Introducing Xi Epoch by Nutanix

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See inside any application infrastructure on any cloud

We are excited to announce the general availability of Xi Epoch, a universal observability and monitoring service for modern cloud applications. Xi Epoch enables DevOps and Site Reliability Engineering (SRE) teams to gain end-to-end visibility into application infrastructure, service interactions, and dependencies. You can now maintain high availability and resilience of your applications without the need for any code instrumentation!

Epoch’s performance-oriented technology and user-centered design make it easy for the users to identify root-causes in real-time and track key service level objectives (SLOs) with out-of-the-box alerts for service level indicators (SLIs) such as latency, traffic, error rates, and saturation.

Application architectures are going through a paradigm shift. Monolithic architectures are giving way to loosely-coupled, API driven microservices based architectures. Applications are increasingly becoming distributed and relying on external services like open-source components, external SaaS providers, and solutions provided by different public cloud vendors, where code-instrumentation is not possible. This creates critical blind spots in monitoring the health and performance of modern distributed applications. As a result, code-centric techniques are becoming ineffective as compared to a service-interaction centric approach that Epoch has championed.

Using network as the vantage point, Epoch can continue to observe and monitor applications as they go through architectural transitions. This makes our approach ‘future proof’ compared with the code-based monitoring approaches. Epoch is especially powerful for Kubernetes and Docker-based microservices applications. DevOps teams can visualize their applications at multiple levels by creating maps of hosts, namespaces, services, and pods. From the application maps, they can drill down and quickly diagnose a range of complex issues such as service configuration (e.g. Kubernetes DNS errors), service reachability issues (e.g. HTTP errors) and service creation problems (e.g. pod scheduling errors).

Application infrastructure components are increasingly becoming dynamic. While VMs used to have life-span of months, now containers persist for a few minutes and server-less compute units such as AWS Lambda persist only for seconds! Such dynamic application structure along with increased application scale has resulted in an explosion of metrics that need to be processed for efficient monitoring. Also, we now have a plethora of options for programming languages and frameworks for applications development. With the advent of microservices and DevOps, companies are increasingly adopting multiple languages (Python, Go, Java, PHP, etc.), frameworks (Node.js, Mesos, Kubernetes, Spark, Hadoop, etc.) and databases (Cassandra, MongoDB, Influx DB, etc.). It is simply not sustainable and practical to code-instrument all these languages and frameworks.

A key benefit of Epoch is that it does not require any code change to generate maps and metrics. It monitors the service interactions and conducts a real-time analysis of packets to obtain deep application insights. As a result, it gives you visibility into everything that “hits the wire” including calls to external services such as AWS RDS, AWS DynamoDB, API calls to Google Maps, Salesforce, Stripe, Twilio, etc.

In contrast to Epoch’s code-agnostic approach, traditional Application Performance Monitoring (APM) products are inflexible and dependent on programming languages since they rely on code-instrumentation techniques. With traditional APM, each service written in an unsupported programming language becomes a blind spot. Moreover, there is a wide range of critical services such as databases, load balancers, service discovery and DNS, that cannot be instrumented using an APM. Built for the monolithic Java and .NET era, the traditional APM techniques are a liability for the polyglot, fast-changing world of public clouds and containers.

Epoch’s auto-discovered maps and deep analytics elegantly address these challenges without relying on code changes or instrumentation. It gives you the ability to see inside any application or solution stack, at scale, on any cloud.

Some of the common use cases for Epoch include application monitoring, incident response, and capacity planning. It also gives you the intelligence to better manage deployments, scaling events and application or infrastructure migrations. Epoch can be used with any public or private cloud, including Nutanix Enterprise Cloud, AWS, Azure, and Google Cloud Platform, and supports almost all popular containerized and non-containerized application environments including Kubernetes, Docker, Mesos, Debian, Ubuntu, and CentOS. Epoch is available today as a public SaaS solution. The self-hosted and on-prem options will be available soon.

Epoch has these three key components:

  • Collectors: The collectors are lightweight agents that are deployed on the machines serving your cloud application. They capture, in almost real time, the network packets, infrastructure, and custom metrics. This data is then shipped to the stream processor.
  • Stream Processors: The stream processors can be installed alongside the collector or the AOC [Application Operations Center], or as a standalone installation. The stream processor receives data from collectors, processing it into compact time series metrics which are then shipped to the AOC.
  • AOC (Application Operations Center): The AOC is the user interface for monitoring, visualizing, querying, and debugging of application infrastructure. The Epoch AOC has many key functionalities:
  • AOC Maps: Provides a Google Maps-like experience for your cloud applications. It generates maps which automatically discover every Docker container, Kubernetes pod, host, and service endpoint, along with all the interactions amongst them. Maps also capture key service health metrics of latency, throughput and error rates for API calls, database queries, DNS lookups, and several other service interactions. You also get the flexibility to not only use the out-of-the-box maps but also customize your own map with Group-by and Filter options. You can also perform operations such as zoom in/out and change the time window and duration with a slider.
  • AOC Analytics Sandbox: The Analytics Sandbox is a powerful, real-time analytics engine that can be used to build queries and gain insights into the health of application components. It also powers the workflows for alerts, dashboards, and incident response.
  • AOC Dashboards: AOC provides out-of-the-box dashboards and the ability to customize them based on user needs. These dashboards help identify point-in-time values and meaningful attributes of the data source (e.g. DNS domain types or HTTP status codes). The AOC also enables you to drill down into selected series for swift analysis and debugging.

Available Now

To learn more about Xi Epoch, please see Xi Epoch documentation.


Forward-Looking Statements Disclaimer

This blog includes forward-looking statements including but not limited to the availability of certain product features. These forward-looking statements are not historical facts, and instead are based on our current expectations, estimates, opinions and beliefs. The accuracy of such forward-looking statements depends upon future events, and involves risks, uncertainties and other factors beyond our control that may cause these statements to be inaccurate and cause our actual results, performance or achievements to differ materially and adversely from those anticipated or implied by such statements, including, among others: the failure to integrate our products with our partner’s products and the possibility that we may not receive anticipated results from forming such partnerships; the introduction, or acceleration of adoption of, competing solutions, including public cloud infrastructure; a shift in industry or competitive dynamics or customer demand; and other risks detailed in our Form 10-K for the fiscal year ended July 31, 2018, filed with the Securities and Exchange Commission. These forward-looking statements speak only as of the date of this presentation and, except as required by law, we assume no obligation to update forward-looking statements to reflect actual results or subsequent events or circumstances.

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