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Pablo Lalloni

SoftNAS Managed Cloud Storage - 0 views

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    SoftNAS™ is business-class network attached storage (NAS) delivered as software as a service.  The NAS software virtual appliance runs within your cloud computing environment (e.g., Amazon EC2) or local virtual server environment (e.g., VMware vSphere) and manages the available raw disk storage, providing enterprise-grade storage capabilities. SoftNAS leverages a number of open source technologies, including ZFS on Linux.  ZFS on Linux is a port of the popular ZFS filesystem originally produced by Sun Microsystems and released with OpenSolaris.  SoftNAS builds on the robust, solid foundation of ZFS and its powerful, extensible Linux foundation.
Pablo Lalloni

graymeta/stow: Cloud storage abstraction package for Go - 1 views

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    "Cloud storage abstraction package for Go"
Pablo Lalloni

Peter Bourgon · OK Log - 1 views

  • Taking a cue from Prometheus, we invert typical replication from push to pull. Concretely, all ingest and storage nodes join a cluster, and gossip knowledge of each other. All storage nodes consume segments regularly and randomly from all ingest nodes. Consumed segments are merged and, after they reach a certain age or size, replicated across other storage nodes. Only once they are successfully replicated are the original segments confirmed and cleared from the ingest nodes.
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    "OK Log is a distributed and coördination-free log management system for big ol' clusters. I built it from first principles, to teach myself the gory details of shuffling logs around. This is the story of the prototype."
Pablo Lalloni

Introduction - Terraform - 2 views

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    "Terraform is a tool for building, changing, and versioning infrastructure safely and efficiently. Terraform can manage existing and popular service providers as well as custom in-house solutions. Configuration files describe to Terraform the components needed to run a single application or your entire datacenter. Terraform generates an execution plan describing what it will do to reach the desired state, and then executes it to build the described infrastructure. As the configuration changes, Terraform is able to determine what changed and create incremental execution plans which can be applied. The infrastructure Terraform can manage includes low-level components such as compute instances, storage, and networking, as well as high-level components such as DNS entries, SaaS features, etc."
Pablo Lalloni

Features - Firebase - 0 views

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    "Firebase can power your app's backend, including data storage, user authentication, static hosting, and more."
Pablo Lalloni

Google Container Registry - Tools - Google Cloud Platform - 0 views

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    "Google Container Registry provides secure, private Docker image storage on Google Cloud Platform. While Docker provides a central registry to store public images, you may not want your images to be accessible to the world. In this case, you must use a private registry. The Google Container Registry runs on Google Cloud Platform, so can be relied upon for consistent uptime and security. The registry can be accessed through an HTTPS endpoint, so you can pull images from any machine, whether it's a Google Compute Engine instance or your own hardware."
Pablo Lalloni

Introduction - Terraform - 2 views

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    "Terraform is a tool for building, changing, and versioning infrastructure safely and efficiently. Terraform can manage existing and popular service providers as well as custom in-house solutions. Configuration files describe to Terraform the components needed to run a single application or your entire datacenter. Terraform generates an execution plan describing what it will do to reach the desired state, and then executes it to build the described infrastructure. As the configuration changes, Terraform is able to determine what changed and create incremental execution plans which can be applied. The infrastructure Terraform can manage includes low-level components such as compute instances, storage, and networking, as well as high-level components such as DNS entries, SaaS features, etc. The key features of Terraform are: Infrastructure as Code: Infrastructure is described using a high-level configuration syntax. This allows a blueprint of your datacenter to be versioned and treated as you would any other code. Additionally, infrastructure can be shared and re-used. Execution Plans: Terraform has a "planning" step where it generates an execution plan. The execution plan shows what Terraform will do when you call apply. This lets you avoid any surprises when Terraform manipulates infrastructure. Resource Graph: Terraform builds a graph of all your resources, and parallelizes the creation and modification of any non-dependent resources. Because of this, Terraform builds infrastructure as efficiently as possible, and operators get insight into dependencies in their infrastructure. Change Automation: Complex changesets can be applied to your infrastructure with minimal human interaction. With the previously mentioned execution plan and resource graph, you know exactly what Terraform will change and in what order, avoiding many possible human errors."
Pablo Lalloni

Portable Cloud Programming with Go Cloud - The Go Blog - 0 views

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    "We have identified common services used by cloud applications and have created generic APIs to work across cloud providers. Today, Go Cloud is launching with blob storage, MySQL database access, runtime configuration, and an HTTP server configured with request logging, tracing, and health checking. Go Cloud offers support for Google Cloud Platform (GCP) and Amazon Web Services (AWS). We plan to work with cloud industry partners and the Go community to add support for additional cloud providers very soon. "
Pablo Lalloni

The HDF Group - Why use HDF? - 0 views

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    "HDF (Hierarchical Data Format) technologies are relevant when the data challenges being faced push the limits of what can be addressed by traditional database systems, XML documents, or in-house data formats. Leveraging the powerful HDF products and the expertise of The HDF Group, organizations realize substantial cost savings while solving challenges that seemed intractable using other data management technologies. Many HDF adopters have very large datasets, very fast access requirements, or very complex datasets. Others turn to HDF because it allows them to easily share data across a wide variety of computational platforms using applications written in different programming languages. Some use HDF to take advantage of the many open-source and commercial tools that understand HDF. Similar to XML documents, HDF files are self-describing and allow users to specify complex data relationships and dependencies. In contrast to XML documents, HDF files can contain binary data (in many representations) and allow direct access to parts of the file without first parsing the entire contents. HDF, not surprisingly, allows hierarchical data objects to be expressed in a very natural manner, in contrast to the tables of relational database. Whereas relational databases support tables, HDF supports n-dimensional datasets and each element in the dataset may itself be a complex object. Relational databases offer excellent support for queries based on field matching, but are not well-suited for sequentially processing all records in the database or for subsetting the data based on coordinate-style lookup."
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