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"Splunk Enterprise is the industry-leading platform for operational intelligence. Collect and index any machine data from virtually any source in real time. Search, monitor, analyze and visualize your data to gain new insights and intelligence. Index everything for deep visibility, forensics and troubleshooting. Work smarter as you and your team share searches and add knowledge specific to your organization. Create ad hoc reports to identify trends or prove compliance controls. Create interactive dashboards to monitor for security incidents, service levels and other key performance metrics. Analyze user transactions, customer behavior, machine behavior, security threats and fraudulent activity, all in real time."

What is Graphite? Graphite is a highly scalable real-time graphing system. As a user, you write an application that collects numeric time-series data that you are interested in graphing, and send it to Graphite's processing backend, carbon, which stores the data in Graphite's specialized database. The data can then be visualized through graphite's web interfaces. Who should use Graphite? Graphite is actually a bit of a niche application. Specifically, it is designed to handle numeric time-series data. For example, Graphite would be good at graphing stock prices because they are numbers that change over time. However Graphite is a complex system, and if you only have a few hundred distinct things you want to graph (stocks prices in the S&P 500) then Graphite is probably overkill. But if you need to graph a lot of different things (like dozens of performance metrics from thousands of servers) and you don't necessarily know the names of those things in advance (who wants to maintain such huge configuration?) then Graphite is for you.

"Saddle is a data manipulation library for Scala that provides array-backed, indexed, one- and two-dimensional data structures that are judiciously specialized on JVM primitives to avoid the overhead of boxing and unboxing. Saddle offers vectorized numerical calculations, automatic alignment of data along indices, robustness to missing (N/A) values, and facilities for I/O. Saddle draws inspiration from several sources, among them the R programming language & statistical environment, the numpy and pandas Python libraries, and the Scala collections library."

"These are the major new features added since Slick 1.0.1: A code generator that reverse-engineers the database schema and generates all code required for working with Slick. New driver architecture to allow support for non-SQL, non-JDBC databases. Table definitions in the Lifted Embedding use a new syntax which is slightly more verbose but also more robust and logical, avoiding several pitfalls from earlier versions. Table definitions (and their * projections) are not restricted to flat tuples of columns anymore. They can use any type that would be valid as the return type of a Query. The old projection concatenation methods ~ and ~: are still supported but not imported by default. In addition to Scala tuples, Slick supports its own HList abstraction for records of arbitrary size. You can also add support for your own record types with only a few lines of code. All record types can be used everywhere (including table definitions and mapped projections) and they can be mixed and nested arbitrarily. Soft inserts are now the default, i.e. AutoInc columns are automatically skipped when inserting with +=, ++=, insert and insertAll. This means that you no longer need separate projections (without the primary key) for inserts. There are separate methods forceInsert and forceInsertAll in JdbcProfile for the old behavior. A new model for pre-compiled queries replaces the old QueryTemplate abstraction. Any query (both, actual collection-valued Query objects and scalar queries) or function from Column types to such a query can now be lifted into a Compiled wrapper. Lifted functions can be applied (without having to recompile the query), and you can use both monadic composition of Compiled values or just get the underlying query and use that for further composition. Pre-compiled queries can now be used for update and delete operations in addition to querying. threadLocalSession has been renamed to dynamicSession and the corresponding methods have distinct names (e.g. w

ScalaMeter is a microbenchmarking and performance regression testing framework for the JVM platform that allows expressing performance tests in a way which is both simple and concise.  It can be used both from Scala and Java. write performance tests in a DSL similar to ScalaTest and ScalaCheck specify test input data specify how test results are collected organize performance tests hierarchically

"This site provides a collection of schemas that webmasters can use to markup HTML pages in ways recognized by major search providers, and that can also be used for structured data interoperability (e.g. in JSON). Search engines including Bing, Google, Yahoo! and Yandex rely on this markup to improve the display of search results, making it easier for people to find the right Web pages."

"The microservices architectural style simplifies implementing individual services. However, connecting, monitoring and securing hundreds or even thousands of microservices is not simple.A service mesh provides a transparent and language-independent way to flexibly and easily automate networking, security, and observation functions. In essence, it decouples development and operations for services.The Istio service mesh is split into 1) a data plane built from Envoy proxies that intercepts traffic and controls communication between services, and 2) a control plane that supports services at runtime by providing policy enforcement, telemetry collection, and certificate rotation.The near-term goal is to launch Istio to 1.0, when the key features will all be in beta (including support for Hybrid environments)The long-term vision is to make Istio ambient."

A collection of MapReduce tasks translated (from Pig, Hive, MapReduce streaming, etc.) into Scalding for comparison.