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張 旭

MongoDB Performance Tuning: Everything You Need to Know - Stackify - 0 views

stackify.com/mongodb-performance-tuning

database mongodb

shared by 張 旭 on 15 Apr 21 - No Cached
  • db.serverStatus().globalLock
  • db.serverStatus().locks
  • globalLock.currentQueue.total: This number can indicate a possible concurrency issue if it’s consistently high. This can happen if a lot of requests are waiting for a lock to be released.
  • ...35 more annotations...
  • globalLock.totalTime: If this is higher than the total database uptime, the database has been in a lock state for too long.
  • Unlike relational databases such as MySQL or PostgreSQL, MongoDB uses JSON-like documents for storing data.
  • Databases operate in an environment that consists of numerous reads, writes, and updates.
  • When a lock occurs, no other operation can read or modify the data until the operation that initiated the lock is finished.
  • locks.deadlockCount: Number of times the lock acquisitions have encountered deadlocks
  • Is the database frequently locking from queries? This might indicate issues with the schema design, query structure, or system architecture.
  • For version 3.2 on, WiredTiger is the default.
  • MMAPv1 locks whole collections, not individual documents.
  • WiredTiger performs locking at the document level.
  • When the MMAPv1 storage engine is in use, MongoDB will use memory-mapped files to store data.
  • All available memory will be allocated for this usage if the data set is large enough.
  • db.serverStatus().mem
  • mem.resident: Roughly equivalent to the amount of RAM in megabytes that the database process uses
  • If mem.resident exceeds the value of system memory and there’s a large amount of unmapped data on disk, we’ve most likely exceeded system capacity.
  • If the value of mem.mapped is greater than the amount of system memory, some operations will experience page faults.
  • The WiredTiger storage engine is a significant improvement over MMAPv1 in performance and concurrency.
  • By default, MongoDB will reserve 50 percent of the available memory for the WiredTiger data cache.
  • wiredTiger.cache.bytes currently in the cache – This is the size of the data currently in the cache.
  • wiredTiger.cache.tracked dirty bytes in the cache – This is the size of the dirty data in the cache.
  • we can look at the wiredTiger.cache.bytes read into cache value for read-heavy applications. If this value is consistently high, increasing the cache size may improve overall read performance.
  • check whether the application is read-heavy. If it is, increase the size of the replica set and distribute the read operations to secondary members of the set.
  • write-heavy, use sharding within a sharded cluster to distribute the load.
  • Replication is the propagation of data from one node to another
  • Replication sets handle this replication.
  • Sometimes, data isn’t replicated as quickly as we’d like.
  • a particularly thorny problem if the lag between a primary and secondary node is high and the secondary becomes the primary
  • use the db.printSlaveReplicationInfo() or the rs.printSlaveReplicationInfo() command to see the status of a replica set from the perspective of the secondary member of the set.
  • shows how far behind the secondary members are from the primary. This number should be as low as possible.
  • monitor this metric closely.
  • watch for any spikes in replication delay.
  • Always investigate these issues to understand the reasons for the lag.
  • One replica set is primary. All others are secondary.
  • it’s not normal for nodes to change back and forth between primary and secondary.
  • use the profiler to gain a deeper understanding of the database’s behavior.
  • Enabling the profiler can affect system performance, due to the additional activity.
  • 張 旭 on 15 Apr 21
     
    "globalLock.currentQueue.total: This number can indicate a possible concurrency issue if it's consistently high. This can happen if a lot of requests are waiting for a lock to be released."
張 旭

Introducing CNAME Flattening: RFC-Compliant CNAMEs at a Domain's Root - 0 views

blog.cloudflare.com/liant-cnames-at-a-domains-root

dns networking

shared by 張 旭 on 15 Mar 22 - No Cached
  • you can now safely use a CNAME record, as opposed to an A record that points to a fixed IP address, as your root record in CloudFlare DNS without triggering a number of edge case error conditions because you’re violating the DNS spec.
  • CNAME Flattening allowed us to use a root domain while still maintaining DNS fault-tolerance across multiple IP addresses.
  • Traditionally, the root record of a domain needed to point to an IP address (known as an A -- for "address" -- Record).
  • ...13 more annotations...
  • WordPlumblr allows its users to use custom domains that point to the WordPlumblr infrastructure
  • A CNAME is an alias. It allows one domain to point to another domain which, eventually if you follow the CNAME chain, will resolve to an A record and IP address.
  • For example, WordPlumblr might have assigned the CNAME 6equj5.wordplumblr.com for Foo.com. Foo.com and the other customers may have all initially resolved, at the end of the CNAME chain, to the same IP address.
  • you usually don't want to address memory directly but, instead, you set up a pointer to a block of memory where you're going to store something. If the operating system needs to move the memory around then it just updates the pointer to point to wherever the chunk of memory has been moved to.
  • CNAMEs work great for subdomains like www.foo.com or blog.foo.com. Unfortunately, they don't work for a naked domain like foo.com itself.
  • the DNS spec enshrined that the root record -- the naked domain without any subdomain -- could not be a CNAME.
  • Technically, the root could be a CNAME but the RFCs state that once a record has a CNAME it can't have any other entries associated with it
  • a way to support a CNAME at the root, but still follow the RFC and return an IP address for any query for the root record.
  • extended our authoritative DNS infrastructure to, in certain cases, act as a kind of DNS resolver.
  • if there's a CNAME at the root, rather than returning that record directly we recurse through the CNAME chain ourselves until we find an A Record.
  • allows the flexibility of having CNAMEs at the root without breaking the DNS specification.
  • We cache the CNAME responses -- respecting the DNS TTLs, just like a recursor should -- which means often we have the answer without having to traverse the chain.
  • CNAME flattening solved email resolution errors for us which was very key.
張 旭

Template Designer Documentation - Jinja2 Documentation (2.10) - 0 views

jinja.pocoo.org/...templates

python jinja template programming

shared by 張 旭 on 18 Feb 19 - No Cached
  • A Jinja template doesn’t need to have a specific extension
  • A Jinja template is simply a text file
  • tags, which control the logic of the template
  • ...106 more annotations...
  • {% ... %} for Statements
  • {{ ... }} for Expressions to print to the template output
  • use a dot (.) to access attributes of a variable
  • the outer double-curly braces are not part of the variable, but the print statement.
  • If you access variables inside tags don’t put the braces around them.
  • If a variable or attribute does not exist, you will get back an undefined value.
  • the default behavior is to evaluate to an empty string if printed or iterated over, and to fail for every other operation.
  • if an object has an item and attribute with the same name. Additionally, the attr() filter only looks up attributes.
  • Variables can be modified by filters. Filters are separated from the variable by a pipe symbol (|) and may have optional arguments in parentheses.
  • Multiple filters can be chained
  • Tests can be used to test a variable against a common expression.
  • add is plus the name of the test after the variable.
  • to find out if a variable is defined, you can do name is defined, which will then return true or false depending on whether name is defined in the current template context.
  • strip whitespace in templates by hand. If you add a minus sign (-) to the start or end of a block (e.g. a For tag), a comment, or a variable expression, the whitespaces before or after that block will be removed
  • not add whitespace between the tag and the minus sign
  • mark a block raw
  • Template inheritance allows you to build a base “skeleton” template that contains all the common elements of your site and defines blocks that child templates can override.
  • The {% extends %} tag is the key here. It tells the template engine that this template “extends” another template.
  • access templates in subdirectories with a slash
  • can’t define multiple {% block %} tags with the same name in the same template
  • use the special self variable and call the block with that name
  • self.title()
  • super()
  • put the name of the block after the end tag for better readability
  • if the block is replaced by a child template, a variable would appear that was not defined in the block or passed to the context.
  • setting the block to “scoped” by adding the scoped modifier to a block declaration
  • If you have a variable that may include any of the following chars (>, <, &, or ") you SHOULD escape it unless the variable contains well-formed and trusted HTML.
  • Jinja2 functions (macros, super, self.BLOCKNAME) always return template data that is marked as safe.
  • With the default syntax, control structures appear inside {% ... %} blocks.
  • the dictsort filter
  • loop.cycle
  • Unlike in Python, it’s not possible to break or continue in a loop
  • use loops recursively
  • add the recursive modifier to the loop definition and call the loop variable with the new iterable where you want to recurse.
  • The loop variable always refers to the closest (innermost) loop.
  • whether the value changed at all,
  • use it to test if a variable is defined, not empty and not false
  • Macros are comparable with functions in regular programming languages.
  • If a macro name starts with an underscore, it’s not exported and can’t be imported.
  • pass a macro to another macro
  • caller()
  • a single trailing newline is stripped if present
  • other whitespace (spaces, tabs, newlines etc.) is returned unchanged
  • a block tag works in “both” directions. That is, a block tag doesn’t just provide a placeholder to fill - it also defines the content that fills the placeholder in the parent.
  • Python dicts are not ordered
  • caller(user)
  • call(user)
  • This is a simple dialog rendered by using a macro and a call block.
  • Filter sections allow you to apply regular Jinja2 filters on a block of template data.
  • Assignments at top level (outside of blocks, macros or loops) are exported from the template like top level macros and can be imported by other templates.
  • using namespace objects which allow propagating of changes across scopes
  • use block assignments to capture the contents of a block into a variable name.
  • The extends tag can be used to extend one template from another.
  • Blocks are used for inheritance and act as both placeholders and replacements at the same time.
  • The include statement is useful to include a template and return the rendered contents of that file into the current namespace
  • Included templates have access to the variables of the active context by default.
  • putting often used code into macros
  • imports are cached and imported templates don’t have access to the current template variables, just the globals by default.
  • Macros and variables starting with one or more underscores are private and cannot be imported.
  • By default, included templates are passed the current context and imported templates are not.
  • imports are often used just as a module that holds macros.
  • Integers and floating point numbers are created by just writing the number down
  • Everything between two brackets is a list.
  • Tuples are like lists that cannot be modified (“immutable”).
  • A dict in Python is a structure that combines keys and values.
  • // Divide two numbers and return the truncated integer result
  • The special constants true, false, and none are indeed lowercase
  • all Jinja identifiers are lowercase
  • (expr) group an expression.
  • The is and in operators support negation using an infix notation
  • in Perform a sequence / mapping containment test.
  • | Applies a filter.
  • ~ Converts all operands into strings and concatenates them.
  • use inline if expressions.
  • always an attribute is returned and items are not looked up.
  • default(value, default_value=u'', boolean=False)¶ If the value is undefined it will return the passed default value, otherwise the value of the variable
  • dictsort(value, case_sensitive=False, by='key', reverse=False)¶ Sort a dict and yield (key, value) pairs.
  • format(value, *args, **kwargs)¶ Apply python string formatting on an object
  • groupby(value, attribute)¶ Group a sequence of objects by a common attribute.
  • grouping by is stored in the grouper attribute and the list contains all the objects that have this grouper in common.
  • indent(s, width=4, first=False, blank=False, indentfirst=None)¶ Return a copy of the string with each line indented by 4 spaces. The first line and blank lines are not indented by default.
  • join(value, d=u'', attribute=None)¶ Return a string which is the concatenation of the strings in the sequence.
  • map()¶ Applies a filter on a sequence of objects or looks up an attribute.
  • pprint(value, verbose=False)¶ Pretty print a variable. Useful for debugging.
  • reject()¶ Filters a sequence of objects by applying a test to each object, and rejecting the objects with the test succeeding.
  • replace(s, old, new, count=None)¶ Return a copy of the value with all occurrences of a substring replaced with a new one.
  • round(value, precision=0, method='common')¶ Round the number to a given precision
  • even if rounded to 0 precision, a float is returned.
  • select()¶ Filters a sequence of objects by applying a test to each object, and only selecting the objects with the test succeeding.
  • sort(value, reverse=False, case_sensitive=False, attribute=None)¶ Sort an iterable. Per default it sorts ascending, if you pass it true as first argument it will reverse the sorting.
  • striptags(value)¶ Strip SGML/XML tags and replace adjacent whitespace by one space.
  • tojson(value, indent=None)¶ Dumps a structure to JSON so that it’s safe to use in <script> tags.
  • trim(value)¶ Strip leading and trailing whitespace.
  • unique(value, case_sensitive=False, attribute=None)¶ Returns a list of unique items from the the given iterable
  • urlize(value, trim_url_limit=None, nofollow=False, target=None, rel=None)¶ Converts URLs in plain text into clickable links.
  • defined(value)¶ Return true if the variable is defined
  • in(value, seq)¶ Check if value is in seq.
  • mapping(value)¶ Return true if the object is a mapping (dict etc.).
  • number(value)¶ Return true if the variable is a number.
  • sameas(value, other)¶ Check if an object points to the same memory address than another object
  • undefined(value)¶ Like defined() but the other way round.
  • A joiner is passed a string and will return that string every time it’s called, except the first time (in which case it returns an empty string).
  • namespace(...)¶ Creates a new container that allows attribute assignment using the {% set %} tag
  • The with statement makes it possible to create a new inner scope. Variables set within this scope are not visible outside of the scope.
  • activate and deactivate the autoescaping from within the templates
  • With both trim_blocks and lstrip_blocks enabled, you can put block tags on their own lines, and the entire block line will be removed when rendered, preserving the whitespace of the contents
張 旭

Volumes - Kubernetes - 0 views

kubernetes.io/...volumes

kubernetes volume disk nfs

shared by 張 旭 on 28 May 19 - No Cached
  • On-disk files in a Container are ephemeral,
  • when a Container crashes, kubelet will restart it, but the files will be lost - the Container starts with a clean state
  • In Docker, a volume is simply a directory on disk or in another Container.
  • ...105 more annotations...
  • A Kubernetes volume, on the other hand, has an explicit lifetime - the same as the Pod that encloses it.
  • a volume outlives any Containers that run within the Pod, and data is preserved across Container restarts.
    • 張 旭
      張 旭 on 06 Jul 19
       
      Kubernetes Volume 是跟著 Pod 的生命週期在走
  • Kubernetes supports many types of volumes, and a Pod can use any number of them simultaneously.
  • To use a volume, a Pod specifies what volumes to provide for the Pod (the .spec.volumes field) and where to mount those into Containers (the .spec.containers.volumeMounts field).
  • A process in a container sees a filesystem view composed from their Docker image and volumes.
  • Volumes can not mount onto other volumes or have hard links to other volumes.
  • Each Container in the Pod must independently specify where to mount each volume
  • localnfs
  • cephfs
  • awsElasticBlockStore
  • glusterfs
  • vsphereVolume
  • An awsElasticBlockStore volume mounts an Amazon Web Services (AWS) EBS Volume into your Pod.
  • the contents of an EBS volume are preserved and the volume is merely unmounted.
  • an EBS volume can be pre-populated with data, and that data can be “handed off” between Pods.
  • create an EBS volume using aws ec2 create-volume
  • the nodes on which Pods are running must be AWS EC2 instances
  • EBS only supports a single EC2 instance mounting a volume
  • check that the size and EBS volume type are suitable for your use!
  • A cephfs volume allows an existing CephFS volume to be mounted into your Pod.
  • the contents of a cephfs volume are preserved and the volume is merely unmounted.
    • 張 旭
      張 旭 on 06 Jul 19
       
      相當於自己的 AWS EBS
  • CephFS can be mounted by multiple writers simultaneously.
  • have your own Ceph server running with the share exported
  • configMap
  • The configMap resource provides a way to inject configuration data into Pods
  • When referencing a configMap object, you can simply provide its name in the volume to reference it
  • volumeMounts: - name: config-vol mountPath: /etc/config volumes: - name: config-vol configMap: name: log-config items: - key: log_level path: log_level
  • create a ConfigMap before you can use it.
  • A Container using a ConfigMap as a subPath volume mount will not receive ConfigMap updates.
  • An emptyDir volume is first created when a Pod is assigned to a Node, and exists as long as that Pod is running on that node.
  • When a Pod is removed from a node for any reason, the data in the emptyDir is deleted forever.
  • By default, emptyDir volumes are stored on whatever medium is backing the node - that might be disk or SSD or network storage, depending on your environment.
  • you can set the emptyDir.medium field to "Memory" to tell Kubernetes to mount a tmpfs (RAM-backed filesystem)
  • volumeMounts: - mountPath: /cache name: cache-volume volumes: - name: cache-volume emptyDir: {}
  • An fc volume allows an existing fibre channel volume to be mounted in a Pod.
  • configure FC SAN Zoning to allocate and mask those LUNs (volumes) to the target WWNs beforehand so that Kubernetes hosts can access them.
  • Flocker is an open-source clustered Container data volume manager. It provides management and orchestration of data volumes backed by a variety of storage backends.
  • emptyDir
  • flocker
  • A flocker volume allows a Flocker dataset to be mounted into a Pod
  • have your own Flocker installation running
  • A gcePersistentDisk volume mounts a Google Compute Engine (GCE) Persistent Disk into your Pod.
  • Using a PD on a Pod controlled by a ReplicationController will fail unless the PD is read-only or the replica count is 0 or 1
  • A glusterfs volume allows a Glusterfs (an open source networked filesystem) volume to be mounted into your Pod.
  • have your own GlusterFS installation running
  • A hostPath volume mounts a file or directory from the host node’s filesystem into your Pod.
  • a powerful escape hatch for some applications
  • access to Docker internals; use a hostPath of /var/lib/docker
  • allowing a Pod to specify whether a given hostPath should exist prior to the Pod running, whether it should be created, and what it should exist as
  • specify a type for a hostPath volume
  • the files or directories created on the underlying hosts are only writable by root.
  • hostPath: # directory location on host path: /data # this field is optional type: Directory
  • An iscsi volume allows an existing iSCSI (SCSI over IP) volume to be mounted into your Pod.
  • have your own iSCSI server running
  • A feature of iSCSI is that it can be mounted as read-only by multiple consumers simultaneously.
  • A local volume represents a mounted local storage device such as a disk, partition or directory.
  • Local volumes can only be used as a statically created PersistentVolume.
  • Compared to hostPath volumes, local volumes can be used in a durable and portable manner without manually scheduling Pods to nodes, as the system is aware of the volume’s node constraints by looking at the node affinity on the PersistentVolume.
  • If a node becomes unhealthy, then the local volume will also become inaccessible, and a Pod using it will not be able to run.
  • PersistentVolume spec using a local volume and nodeAffinity
  • PersistentVolume nodeAffinity is required when using local volumes. It enables the Kubernetes scheduler to correctly schedule Pods using local volumes to the correct node.
  • PersistentVolume volumeMode can now be set to “Block” (instead of the default value “Filesystem”) to expose the local volume as a raw block device.
  • When using local volumes, it is recommended to create a StorageClass with volumeBindingMode set to WaitForFirstConsumer
  • An nfs volume allows an existing NFS (Network File System) share to be mounted into your Pod.
  • NFS can be mounted by multiple writers simultaneously.
  • have your own NFS server running with the share exported
  • A persistentVolumeClaim volume is used to mount a PersistentVolume into a Pod.
  • PersistentVolumes are a way for users to “claim” durable storage (such as a GCE PersistentDisk or an iSCSI volume) without knowing the details of the particular cloud environment.
  • A projected volume maps several existing volume sources into the same directory.
  • All sources are required to be in the same namespace as the Pod. For more details, see the all-in-one volume design document.
  • Each projected volume source is listed in the spec under sources
  • A Container using a projected volume source as a subPath volume mount will not receive updates for those volume sources.
  • RBD volumes can only be mounted by a single consumer in read-write mode - no simultaneous writers allowed
  • A secret volume is used to pass sensitive information, such as passwords, to Pods
  • store secrets in the Kubernetes API and mount them as files for use by Pods
  • secret volumes are backed by tmpfs (a RAM-backed filesystem) so they are never written to non-volatile storage.
  • create a secret in the Kubernetes API before you can use it
  • A Container using a Secret as a subPath volume mount will not receive Secret updates.
  • StorageOS runs as a Container within your Kubernetes environment, making local or attached storage accessible from any node within the Kubernetes cluster.
  • Data can be replicated to protect against node failure. Thin provisioning and compression can improve utilization and reduce cost.
  • StorageOS provides block storage to Containers, accessible via a file system.
  • A vsphereVolume is used to mount a vSphere VMDK Volume into your Pod.
  • supports both VMFS and VSAN datastore.
  • create VMDK using one of the following methods before using with Pod.
  • share one volume for multiple uses in a single Pod.
  • The volumeMounts.subPath property can be used to specify a sub-path inside the referenced volume instead of its root.
  • volumeMounts: - name: workdir1 mountPath: /logs subPathExpr: $(POD_NAME)
  • env: - name: POD_NAME valueFrom: fieldRef: apiVersion: v1 fieldPath: metadata.name
  • Use the subPathExpr field to construct subPath directory names from Downward API environment variables
  • enable the VolumeSubpathEnvExpansion feature gate
  • The subPath and subPathExpr properties are mutually exclusive.
  • There is no limit on how much space an emptyDir or hostPath volume can consume, and no isolation between Containers or between Pods.
  • emptyDir and hostPath volumes will be able to request a certain amount of space using a resource specification, and to select the type of media to use, for clusters that have several media types.
  • the Container Storage Interface (CSI) and Flexvolume. They enable storage vendors to create custom storage plugins without adding them to the Kubernetes repository.
  • all volume plugins (like volume types listed above) were “in-tree” meaning they were built, linked, compiled, and shipped with the core Kubernetes binaries and extend the core Kubernetes API.
  • Container Storage Interface (CSI) defines a standard interface for container orchestration systems (like Kubernetes) to expose arbitrary storage systems to their container workloads.
  • Once a CSI compatible volume driver is deployed on a Kubernetes cluster, users may use the csi volume type to attach, mount, etc. the volumes exposed by the CSI driver.
  • The csi volume type does not support direct reference from Pod and may only be referenced in a Pod via a PersistentVolumeClaim object.
  • This feature requires CSIInlineVolume feature gate to be enabled:--feature-gates=CSIInlineVolume=true
  • In-tree plugins that support CSI Migration and have a corresponding CSI driver implemented are listed in the “Types of Volumes” section above.
  • Mount propagation allows for sharing volumes mounted by a Container to other Containers in the same Pod, or even to other Pods on the same node.
  • Mount propagation of a volume is controlled by mountPropagation field in Container.volumeMounts.
  • HostToContainer - This volume mount will receive all subsequent mounts that are mounted to this volume or any of its subdirectories.
  • Bidirectional - This volume mount behaves the same the HostToContainer mount. In addition, all volume mounts created by the Container will be propagated back to the host and to all Containers of all Pods that use the same volume.
  • Edit your Docker’s systemd service file. Set MountFlags as follows:MountFlags=shared
crazylion lee

Apache Geode (incubating) | Home - 0 views

geode.incubator.apache.org

apache in-memory db

shared by crazylion lee on 30 Nov 15 - No Cached
  • crazylion lee on 30 Nov 15
     
    "Geode is an open source, distributed, in-memory database for scale-out applications."
張 旭

The Twelve-Factor App - 0 views

12factor.net/processes

development application programming

shared by 張 旭 on 20 Feb 19 - No Cached
  • stateless processes
  • a production deploy of a sophisticated app may use many process types, instantiated into zero or more running processes.
  • Twelve-factor processes are stateless and share-nothing.
  • ...6 more annotations...
  • Any data that needs to persist must be stored in a stateful backing service, typically a database.
  • The memory space or filesystem of the process can be used as a brief, single-transaction cache.
  • wipe out all local (e.g., memory and filesystem) state
  • compiling during the build stage
  • “sticky sessions” – that is, caching user session data in memory of the app’s process and expecting future requests from the same visitor to be routed to the same process.
  • Sticky sessions are a violation of twelve-factor and should never be used or relied upon
張 旭

Logstash Alternatives: Pros & Cons of 5 Log Shippers [2019] - Sematext - 0 views

sematext.com/...logstash-alternatives

log monitor system logstash fluentd

shared by 張 旭 on 05 Nov 19 - No Cached
  • In this case, Elasticsearch. And because Elasticsearch can be down or struggling, or the network can be down, the shipper would ideally be able to buffer and retry
  • Logstash is typically used for collecting, parsing, and storing logs for future use as part of log management.
  • Logstash’s biggest con or “Achille’s heel” has always been performance and resource consumption (the default heap size is 1GB).
  • ...37 more annotations...
  • This can be a problem for high traffic deployments, when Logstash servers would need to be comparable with the Elasticsearch ones.
  • Filebeat was made to be that lightweight log shipper that pushes to Logstash or Elasticsearch.
  • differences between Logstash and Filebeat are that Logstash has more functionality, while Filebeat takes less resources.
  • Filebeat is just a tiny binary with no dependencies.
  • For example, how aggressive it should be in searching for new files to tail and when to close file handles when a file didn’t get changes for a while.
  • For example, the apache module will point Filebeat to default access.log and error.log paths
  • Filebeat’s scope is very limited,
  • Initially it could only send logs to Logstash and Elasticsearch, but now it can send to Kafka and Redis, and in 5.x it also gains filtering capabilities.
  • Filebeat can parse JSON
  • you can push directly from Filebeat to Elasticsearch, and have Elasticsearch do both parsing and storing.
  • You shouldn’t need a buffer when tailing files because, just as Logstash, Filebeat remembers where it left off
  • For larger deployments, you’d typically use Kafka as a queue instead, because Filebeat can talk to Kafka as well
  • The default syslog daemon on most Linux distros, rsyslog can do so much more than just picking logs from the syslog socket and writing to /var/log/messages.
  • It can tail files, parse them, buffer (on disk and in memory) and ship to a number of destinations, including Elasticsearch.
  • rsyslog is the fastest shipper
  • Its grammar-based parsing module (mmnormalize) works at constant speed no matter the number of rules (we tested this claim).
  • use it as a simple router/shipper, any decent machine will be limited by network bandwidth
  • It’s also one of the lightest parsers you can find, depending on the configured memory buffers.
  • rsyslog requires more work to get the configuration right
  • the main difference between Logstash and rsyslog is that Logstash is easier to use while rsyslog lighter.
  • rsyslog fits well in scenarios where you either need something very light yet capable (an appliance, a small VM, collecting syslog from within a Docker container).
  • rsyslog also works well when you need that ultimate performance.
  • syslog-ng as an alternative to rsyslog (though historically it was actually the other way around).
  • a modular syslog daemon, that can do much more than just syslog
  • Unlike rsyslog, it features a clear, consistent configuration format and has nice documentation.
  • Similarly to rsyslog, you’d probably want to deploy syslog-ng on boxes where resources are tight, yet you do want to perform potentially complex processing.
  • syslog-ng has an easier, more polished feel than rsyslog, but likely not that ultimate performance
  • Fluentd was built on the idea of logging in JSON wherever possible (which is a practice we totally agree with) so that log shippers down the line don’t have to guess which substring is which field of which type.
  • Fluentd plugins are in Ruby and very easy to write.
  • structured data through Fluentd, it’s not made to have the flexibility of other shippers on this list (Filebeat excluded).
  • Fluent Bit, which is to Fluentd similar to how Filebeat is for Logstash.
  • Fluentd is a good fit when you have diverse or exotic sources and destinations for your logs, because of the number of plugins.
  • Splunk isn’t a log shipper, it’s a commercial logging solution
  • Graylog is another complete logging solution, an open-source alternative to Splunk.
  • everything goes through graylog-server, from authentication to queries.
  • Graylog is nice because you have a complete logging solution, but it’s going to be harder to customize than an ELK stack.
  • it depends
crazylion lee

Writing a Bootloader | Blog of Osanda - 1 views

osandamalith.wordpress.com/...writing-a-bootloader

bootloader linux c

shared by crazylion lee on 06 Nov 15 - No Cached
  • crazylion lee on 06 Nov 15
     
    "A bootloader is a special program that is executed each time a bootable device is initialized by the computer during its power on or reset that will load the kernel image into the memory. This application is very close to hardware and to the architecture of the CPU. All x86 PCs boot in Real Mode. In this mode you have only 16-bit instructions. Our bootloader runs in Real Mode and our bootloader is a 16-bit program."
張 旭

Rails Routing from the Outside In - Ruby on Rails Guides - 0 views

guides.rubyonrails.org/routing.html

rails router path url namespace

shared by 張 旭 on 09 Mar 14 - Cached
  • Resource routing allows you to quickly declare all of the common routes for a given resourceful controller.
  • Rails would dispatch that request to the destroy method on the photos controller with { id: '17' } in params.
  • a resourceful route provides a mapping between HTTP verbs and URLs to controller actions.
  • ...86 more annotations...
  • each action also maps to particular CRUD operations in a database
  • resource :photo and resources :photos creates both singular and plural routes that map to the same controller (PhotosController).
  • One way to avoid deep nesting (as recommended above) is to generate the collection actions scoped under the parent, so as to get a sense of the hierarchy, but to not nest the member actions.
  • to only build routes with the minimal amount of information to uniquely identify the resource
  • The shallow method of the DSL creates a scope inside of which every nesting is shallow
  • These concerns can be used in resources to avoid code duplication and share behavior across routes
  • add a member route, just add a member block into the resource block
  • You can leave out the :on option, this will create the same member route except that the resource id value will be available in params[:photo_id] instead of params[:id].
  • Singular Resources
  • use a singular resource to map /profile (rather than /profile/:id) to the show action
  • Passing a String to get will expect a controller#action format
  • workaround
  • organize groups of controllers under a namespace
  • route /articles (without the prefix /admin) to Admin::ArticlesController
  • route /admin/articles to ArticlesController (without the Admin:: module prefix)
  • Nested routes allow you to capture this relationship in your routing.
  • helpers take an instance of Magazine as the first parameter (magazine_ads_url(@magazine)).
  • Resources should never be nested more than 1 level deep.
  • via the :shallow option
  • a balance between descriptive routes and deep nesting
  • :shallow_path prefixes member paths with the specified parameter
  • Routing Concerns allows you to declare common routes that can be reused inside other resources and routes
  • Rails can also create paths and URLs from an array of parameters.
  • use url_for with a set of objects
  • In helpers like link_to, you can specify just the object in place of the full url_for call
  • insert the action name as the first element of the array
  • This will recognize /photos/1/preview with GET, and route to the preview action of PhotosController, with the resource id value passed in params[:id]. It will also create the preview_photo_url and preview_photo_path helpers.
  • pass :on to a route, eliminating the block:
  • Collection Routes
  • This will enable Rails to recognize paths such as /photos/search with GET, and route to the search action of PhotosController. It will also create the search_photos_url and search_photos_path route helpers.
  • simple routing makes it very easy to map legacy URLs to new Rails actions
  • add an alternate new action using the :on shortcut
  • When you set up a regular route, you supply a series of symbols that Rails maps to parts of an incoming HTTP request.
  • :controller maps to the name of a controller in your application
  • :action maps to the name of an action within that controller
  • optional parameters, denoted by parentheses
  • This route will also route the incoming request of /photos to PhotosController#index, since :action and :id are
  • use a constraint on :controller that matches the namespace you require
  • dynamic segments don't accept dots
  • The params will also include any parameters from the query string
  • :defaults option.
  • set params[:format] to "jpg"
  • cannot override defaults via query parameters
  • specify a name for any route using the :as option
  • create logout_path and logout_url as named helpers in your application.
  • Inside the show action of UsersController, params[:username] will contain the username for the user.
  • should use the get, post, put, patch and delete methods to constrain a route to a particular verb.
  • use the match method with the :via option to match multiple verbs at once
  • Routing both GET and POST requests to a single action has security implications
  • 'GET' in Rails won't check for CSRF token. You should never write to the database from 'GET' requests
  • use the :constraints option to enforce a format for a dynamic segment
  • constraints
  • don't need to use anchors
  • Request-Based Constraints
  • the same name as the hash key and then compare the return value with the hash value.
  • constraint values should match the corresponding Request object method return type
    • 張 旭
      張 旭 on 11 Apr 16
       
      應該就是檢查來源的 request， 如果是某個特定的 request 來訪問的，就通過。
  • blacklist
    • 張 旭
      張 旭 on 11 Apr 16
       
      這裡有點複雜 ...
  • redirect helper
  • reuse dynamic segments from the match in the path to redirect
  • this redirection is a 301 "Moved Permanently" redirect.
  • root method
  • put the root route at the top of the file
  • The root route only routes GET requests to the action.
  • root inside namespaces and scopes
  • For namespaced controllers you can use the directory notation
  • Only the directory notation is supported
  • use the :constraints option to specify a required format on the implicit id
  • specify a single constraint to apply to a number of routes by using the block
  • non-resourceful routes
  • :id parameter doesn't accept dots
  • :as option lets you override the normal naming for the named route helpers
  • use the :as option to prefix the named route helpers that Rails generates for a rout
  • prevent name collisions
  • prefix routes with a named parameter
  • This will provide you with URLs such as /bob/articles/1 and will allow you to reference the username part of the path as params[:username] in controllers, helpers and views
  • :only option
  • :except option
  • generate only the routes that you actually need can cut down on memory use and speed up the routing process.
  • alter path names
  • http://localhost:3000/rails/info/routes
  • rake routes
  • setting the CONTROLLER environment variable
  • Routes should be included in your testing strategy
  • assert_generates assert_recognizes assert_routing
張 旭

2. Swoole Structure · swooletw/laravel-swoole Wiki - 0 views

github.com/...2.-Swoole-Structure

php swoole performance

shared by 張 旭 on 24 Apr 19 - No Cached
  • Laravel application will exist in Worker processes.
  • means Laravel can be stored and kept in memory.
  • Laravel application will exist in the memory and only initialize at the first time. Any changes you did to Laravel will be kept unless you reset them by yourself.
  • 張 旭 on 24 Apr 19
     
    "Laravel application will exist in Worker processes. "
crazylion lee

Riemann - A network monitoring system - 0 views

riemann.io/index.html

monitoring dashboard sysadmin

shared by crazylion lee on 17 Apr 16 - No Cached
  • crazylion lee on 17 Apr 16
     
    "Riemann aggregates events from your servers and applications with a powerful stream processing language. Send an email for every exception in your app. Track the latency distribution of your web app. See the top processes on any host, by memory and CPU. Combine statistics from every Riak node in your cluster and forward to Graphite. Track user activity from second to second."
張 旭

Queues - Laravel - The PHP Framework For Web Artisans - 0 views

laravel.com/queues

php programming laravel queue worker framework

shared by 張 旭 on 02 Mar 19 - No Cached
  • Laravel queues provide a unified API across a variety of different queue backends, such as Beanstalk, Amazon SQS, Redis, or even a relational database.
  • The queue configuration file is stored in config/queue.php
  • a synchronous driver that will execute jobs immediately (for local use)
  • ...56 more annotations...
  • A null queue driver is also included which discards queued jobs.
  • In your config/queue.php configuration file, there is a connections configuration option.
  • any given queue connection may have multiple "queues" which may be thought of as different stacks or piles of queued jobs.
  • each connection configuration example in the queue configuration file contains a queue attribute.
  • if you dispatch a job without explicitly defining which queue it should be dispatched to, the job will be placed on the queue that is defined in the queue attribute of the connection configuration
  • pushing jobs to multiple queues can be especially useful for applications that wish to prioritize or segment how jobs are processed
  • specify which queues it should process by priority.
  • If your Redis queue connection uses a Redis Cluster, your queue names must contain a key hash tag.
  • ensure all of the Redis keys for a given queue are placed into the same hash slot
  • all of the queueable jobs for your application are stored in the app/Jobs directory.
  • Job classes are very simple, normally containing only a handle method which is called when the job is processed by the queue.
  • we were able to pass an Eloquent model directly into the queued job's constructor. Because of the SerializesModels trait that the job is using, Eloquent models will be gracefully serialized and unserialized when the job is processing.
  • When the job is actually handled, the queue system will automatically re-retrieve the full model instance from the database.
  • The handle method is called when the job is processed by the queue
  • The arguments passed to the dispatch method will be given to the job's constructor
  • delay the execution of a queued job, you may use the delay method when dispatching a job.
  • dispatch a job immediately (synchronously), you may use the dispatchNow method.
  • When using this method, the job will not be queued and will be run immediately within the current process
  • specify a list of queued jobs that should be run in sequence.
  • Deleting jobs using the $this->delete() method will not prevent chained jobs from being processed. The chain will only stop executing if a job in the chain fails.
  • this does not push jobs to different queue "connections" as defined by your queue configuration file, but only to specific queues within a single connection.
  • To specify the queue, use the onQueue method when dispatching the job
  • To specify the connection, use the onConnection method when dispatching the job
  • defining the maximum number of attempts on the job class itself.
  • to defining how many times a job may be attempted before it fails, you may define a time at which the job should timeout.
  • using the funnel method, you may limit jobs of a given type to only be processed by one worker at a time
  • using the throttle method, you may throttle a given type of job to only run 10 times every 60 seconds.
  • If an exception is thrown while the job is being processed, the job will automatically be released back onto the queue so it may be attempted again.
  • dispatch a Closure. This is great for quick, simple tasks that need to be executed outside of the current request cycle
  • When dispatching Closures to the queue, the Closure's code contents is cryptographically signed so it can not be modified in transit.
  • Laravel includes a queue worker that will process new jobs as they are pushed onto the queue.
  • once the queue:work command has started, it will continue to run until it is manually stopped or you close your terminal
  • queue workers are long-lived processes and store the booted application state in memory.
  • they will not notice changes in your code base after they have been started.
  • during your deployment process, be sure to restart your queue workers.
  • customize your queue worker even further by only processing particular queues for a given connection
  • The --once option may be used to instruct the worker to only process a single job from the queue
  • The --stop-when-empty option may be used to instruct the worker to process all jobs and then exit gracefully.
  • Daemon queue workers do not "reboot" the framework before processing each job.
  • you should free any heavy resources after each job completes.
  • Since queue workers are long-lived processes, they will not pick up changes to your code without being restarted.
  • restart the workers during your deployment process.
  • php artisan queue:restart
  • The queue uses the cache to store restart signals
  • the queue workers will die when the queue:restart command is executed, you should be running a process manager such as Supervisor to automatically restart the queue workers.
  • each queue connection defines a retry_after option. This option specifies how many seconds the queue connection should wait before retrying a job that is being processed.
  • The --timeout option specifies how long the Laravel queue master process will wait before killing off a child queue worker that is processing a job.
  • When jobs are available on the queue, the worker will keep processing jobs with no delay in between them.
  • While sleeping, the worker will not process any new jobs - the jobs will be processed after the worker wakes up again
  • the numprocs directive will instruct Supervisor to run 8 queue:work processes and monitor all of them, automatically restarting them if they fail.
  • Laravel includes a convenient way to specify the maximum number of times a job should be attempted.
  • define a failed method directly on your job class, allowing you to perform job specific clean-up when a failure occurs.
  • a great opportunity to notify your team via email or Slack.
  • php artisan queue:retry all
  • php artisan queue:flush
  • When injecting an Eloquent model into a job, it is automatically serialized before being placed on the queue and restored when the job is processed
張 旭

Considerations for large clusters | Kubernetes - 0 views

kubernetes.io/...cluster-large

kubernetes

shared by 張 旭 on 24 Mar 22 - No Cached
  • A cluster is a set of nodes (physical or virtual machines) running Kubernetes agents, managed by the control plane.
  • Kubernetes v1.23 supports clusters with up to 5000 nodes.
  • criteria: No more than 110 pods per node No more than 5000 nodes No more than 150000 total pods No more than 300000 total containers
  • ...14 more annotations...
  • In-use IP addresses
  • run one or two control plane instances per failure zone, scaling those instances vertically first and then scaling horizontally after reaching the point of falling returns to (vertical) scale.
  • Kubernetes nodes do not automatically steer traffic towards control-plane endpoints that are in the same failure zone
  • store Event objects in a separate dedicated etcd instance.
  • start and configure additional etcd instance
  • Kubernetes resource limits help to minimize the impact of memory leaks and other ways that pods and containers can impact on other components.
  • Addons' default limits are typically based on data collected from experience running each addon on small or medium Kubernetes clusters.
  • When running on large clusters, addons often consume more of some resources than their default limits.
  • Many addons scale horizontally - you add capacity by running more pods
  • The VerticalPodAutoscaler can run in recommender mode to provide suggested figures for requests and limits.
  • Some addons run as one copy per node, controlled by a DaemonSet: for example, a node-level log aggregator.
  • VerticalPodAutoscaler is a custom resource that you can deploy into your cluster to help you manage resource requests and limits for pods.
  • The cluster autoscaler integrates with a number of cloud providers to help you run the right number of nodes for the level of resource demand in your cluster.
  • The addon resizer helps you in resizing the addons automatically as your cluster's scale changes.
張 旭

JSON Web Token Introduction - jwt.io - 0 views

jwt.io/introduction

javascript jwt authorization authentication oauth security

shared by 張 旭 on 24 Apr 18 - No Cached
  • a stateless authentication mechanism as the user state is never saved in server memory
  • In authentication, when the user successfully logs in using their credentials, a JSON Web Token will be returned and must be saved locally (typically in local storage, but cookies can be also used), instead of the traditional approach of creating a session in the server and returning a cookie.
  • ser agent should send the JWT, typically in the Authorization header using the Bearer schema.
  • ...2 more annotations...
  • It doesn't matter which domains are serving your APIs, so Cross-Origin Resource Sharing (CORS) won't be an issue as it doesn't use cookies.
  • WT and SAML tokens can use a public/private key pair in the form of a X.509 certificate for signing.
張 旭

Container Runtimes | Kubernetes - 0 views

kubernetes.io/...container-runtimes

kubernetes container docker devops

shared by 張 旭 on 25 Jan 23 - No Cached
  • Kubernetes releases before v1.24 included a direct integration with Docker Engine, using a component named dockershim. That special direct integration is no longer part of Kubernetes
  • You need to install a container runtime into each node in the cluster so that Pods can run there.
  • Kubernetes 1.26 requires that you use a runtime that conforms with the Container Runtime Interface (CRI).
  • ...9 more annotations...
  • On Linux, control groups are used to constrain resources that are allocated to processes.
  • Both kubelet and the underlying container runtime need to interface with control groups to enforce resource management for pods and containers and set resources such as cpu/memory requests and limits.
  • When the cgroupfs driver is used, the kubelet and the container runtime directly interface with the cgroup filesystem to configure cgroups.
  • The cgroupfs driver is not recommended when systemd is the init system
  • When systemd is chosen as the init system for a Linux distribution, the init process generates and consumes a root control group (cgroup) and acts as a cgroup manager.
  • Two cgroup managers result in two views of the available and in-use resources in the system.
  • Changing the cgroup driver of a Node that has joined a cluster is a sensitive operation. If the kubelet has created Pods using the semantics of one cgroup driver, changing the container runtime to another cgroup driver can cause errors when trying to re-create the Pod sandbox for such existing Pods. Restarting the kubelet may not solve such errors.
  • The approach to mitigate this instability is to use systemd as the cgroup driver for the kubelet and the container runtime when systemd is the selected init system.
  • Kubernetes 1.26 defaults to using v1 of the CRI API. If a container runtime does not support the v1 API, the kubelet falls back to using the (deprecated) v1alpha2 API instead.
張 旭

How to Benchmark Performance of MySQL & MariaDB Using SysBench | Severalnines - 1 views

severalnines.com/...e-mysql-mariadb-using-sysbench

database mysql performance

shared by 張 旭 on 22 Oct 20 - No Cached
  • SysBench is a C binary which uses LUA scripts to execute benchmarks
  • support for parallelization in the LUA scripts, multiple queries can be executed in parallel
  • by default, benchmarks which cover most of the cases - OLTP workloads, read-only or read-write, primary key lookups and primary key updates.
  • ...21 more annotations...
  • SysBench is not a tool which you can use to tune configurations of your MySQL servers (unless you prepared LUA scripts with custom workload or your workload happen to be very similar to the benchmark workloads that SysBench comes with)
  • it is great for is to compare performance of different hardware.
  • Every new server acquired should go through a warm-up period during which you will stress it to pinpoint potential hardware defects
  • by executing OLTP workload which overloads the server, or you can also use dedicated benchmarks for CPU, disk and memory.
  • bulk_insert.lua. This test can be used to benchmark the ability of MySQL to perform multi-row inserts.
  • All oltp_* scripts share a common table structure. First two of them (oltp_delete.lua and oltp_insert.lua) execute single DELETE and INSERT statements.
  • oltp_point_select, oltp_update_index and oltp_update_non_index. These will execute a subset of queries - primary key-based selects, index-based updates and non-index-based updates.
  • you can run different workload patterns using the same benchmark.
  • Warmup helps to identify “regular” throughput by executing benchmark for a predefined time, allowing to warm up the cache, buffer pools etc.
  • By default SysBench will attempt to execute queries as fast as possible. To simulate slower traffic this option may be used. You can define here how many transactions should be executed per second.
  • SysBench gives you ability to generate different types of data distribution.
  • decide if SysBench should use prepared statements (as long as they are available in the given datastore - for MySQL it means PS will be enabled by default) or not.
  • sysbench ./sysbench/src/lua/oltp_read_write.lua  help
  • By default, SysBench will attempt to execute queries in explicit transaction. This way the dataset will stay consistent and not affected: SysBench will, for example, execute INSERT and DELETE on the same row, making sure the data set will not grow (impacting your ability to reproduce results).
  • specify error codes from MySQL which SysBench should ignore (and not kill the connection).
  • the two most popular benchmarks - OLTP read only and OLTP read/write.
  • 1 million rows will result in ~240 MB of data. Ten tables, 1000 000 rows each equals to 2.4GB
  • by default, SysBench looks for ‘sbtest’ schema which has to exist before you prepare the data set. You may have to create it manually.
  • pass ‘--histogram’ argument to SysBench
  • ~48GB of data (20 tables, 10 000 000 rows each).
  • if you don’t understand why the performance was like it was, you may draw incorrect conclusions out of the benchmarks.
張 旭

How services work | Docker Documentation - 0 views

docs.docker.com/...services

docker swarm cluster system

shared by 張 旭 on 07 Sep 18 - No Cached
  • a service is the image for a microservice within the context of some larger application.
  • When you create a service, you specify which container image to use and which commands to execute inside running containers.
  • an overlay network for the service to connect to other services in the swarm
  • ...13 more annotations...
  • In the swarm mode model, each task invokes exactly one container
  • A task is analogous to a “slot” where the scheduler places a container.
  • A task is the atomic unit of scheduling within a swarm.
  • A task is a one-directional mechanism. It progresses monotonically through a series of states: assigned, prepared, running, etc.
  • Docker swarm mode is a general purpose scheduler and orchestrator.
  • Hypothetically, you could implement other types of tasks such as virtual machine tasks or non-containerized process tasks.
  • If all nodes are paused or drained, and you create a service, it is pending until a node becomes available.
  • reserve a specific amount of memory for a service.
  • impose placement constraints on the service
  • As the administrator of a swarm, you declare the desired state of your swarm, and the manager works with the nodes in the swarm to create that state.
  • two types of service deployments, replicated and global.
  • A global service is a service that runs one task on every node.
  • Good candidates for global services are monitoring agents, an anti-virus scanners or other types of containers that you want to run on every node in the swarm.
張 旭

What are Docker : images? - Project Atomic - 0 views

www.projectatomic.io/...at-are-docker-none-none-images

docker system

shared by 張 旭 on 18 Sep 18 - No Cached
  • Now we understand what these <none>:<none> images stand for. They stand for intermediate images and can be seen using docker images -a
  • They don’t result into a disk space problem but it is definitely a screen real estate problem
  • dangling images
  • ...7 more annotations...
  • Another style of <none>:<none> images are the dangling images which can cause disk space problems.
  • In programming languages like Java or Golang a dangling block of memory is a block that is not referenced by any piece of code.
  • a dangling file system layer in Docker is something that is unused and is not being referenced by any images.
  • intermediate images
  • do docker images and see <none>:<none> images in the list, these are dangling images and needs to be pruned.
  • These dangling images are produced as a result of docker build or pull command.
  • docker rmi $(docker images -f "dangling=true" -q)
張 旭

1. Introduction · swooletw/laravel-swoole Wiki - 0 views

github.com/...1.-Introduction

php swoole performance

shared by 張 旭 on 24 Apr 19 - No Cached
  • when you run PHP script every time, PHP needs to initialize modules and launch Zend Engine for your running environment. And your PHP script needs to be compiled to OpCodes and then Zend Engine can finally execute them.
  • in traditional PHP lifecycle, it wastes a bunch of time building and destroying resources for your script execution.
  • have a built-in server on top of Swoole, and all the scripts can be kept in memory after the first load
  • 張 旭 on 24 Apr 19
     
    "when you run PHP script every time, PHP needs to initialize modules and launch Zend Engine for your running environment. And your PHP script needs to be compiled to OpCodes and then Zend Engine can finally execute them."
張 旭

Home · sysown/proxysql Wiki - 0 views

github.com/wiki

mysql database cluster mariadb proxy

shared by 張 旭 on 19 Nov 18 - No Cached
  • bear in mind that the best way to configure ProxySQL is through its admin interface.
  • llow you to control the list of the backend servers, how traffic is routed to them, and other important settings (such as caching, access control, etc)
  • Once you've made modifications to the in-memory data structure, you must load the new configuration to the runtime, or persist the new settings to disk
  • ...4 more annotations...
  • mysql_variables: contains global variables that control the functionality for handling the incoming MySQL traffic.
  • mysql_users: contains rows for the mysql_users table from the admin interface. Basically, these define the users which can connect to the proxy, and the users with which the proxy can connect to the backend servers.
  • mysql_servers: contains rows for the mysql_servers table from the admin interface. Basically, these define the backend servers towards which the incoming MySQL traffic is routed.
  • mysql_query_rules: contains rows for the mysql_query_rules table from the admin interface. Basically, these define the rules used to classify and route the incoming MySQL traffic, according to various criteria (patterns matched, user used to run the query, etc.).
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