Tags: observability*

Observability refers to the ability to understand the internal state of a system by observing its output. It involves monitoring, logging, and tracing various other forms of data collection to gain insights into the system's behavior, performance, and health. In the context of cloud engineering, observability is crucial for maintaining the efficiency and reliability of distributed systems, as it helps identify and diagnose issues, optimize performance, and ensure security. Observability tools, such as Splunk, Honeycomb, and OpenTelemetry, are used to collect and analyze metrics, logs, and traces, enabling capacity planning, root cause analysis and incident response.

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  1. Outlier treatment is a necessary step in data analysis. This article, part 3 of a four-part series, eases the process and provides insights on effective methods and tools for outlier detection.
  2. Hydrolix is a streaming data lake platform designed to handle large amounts of immutable log data at a lower cost than traditional solutions. The platform is particularly well-suited for observability data and offers real-time query performance on terabyte-scale data. Hydrolix uses an ANSI-compliant SQL interface, is schema-based and fully indexed, and is designed for high-cardinality data. It is purpose-built for log data and focuses on data that comes in once and never changes. Hydrolix is currently used by companies in industries like media, gaming, ad tech, and telecom security that require long-term retention of data. The company recently announced a $35 million Series B round, and its technology serves as the basis for Akamai's observability product TrafficPeak. The platform is designed to save costs for companies dealing with billions of transactions a day and terabytes of data, as it can store data for longer periods than traditional solutions like Splunk or Datadog, thereby reducing costs or increasing retention.
  3. A digital twin is a virtual replica of a real-world physical product, system, or process, serving as its digital counterpart for purposes such as simulation, integration, testing, monitoring, and maintenance. The concept originated from NASA in 2010 as an attempt to improve the physical-model simulation of spacecraft. Digital twins exist throughout the entire lifecycle of the physical entity they represent and are the underlying premise for Product Lifecycle Management. In the manufacturing industry, digital twin technology is being extended to the entire manufacturing process, allowing benefits such as virtualization to be extended to domains such as inventory management, machinery crash avoidance, tooling design, troubleshooting, and preventive maintenance. Digital twinning also enables extended reality and spatial computing to be applied not just to the product itself but also to all of the business processes that contribute towards its production.
  4. The article discusses the use of digital twins in scientific research, with a focus on NASA's James Webb Space Telescope (JWST). Engineers at Raytheon, the company responsible for JWST's software and flight operations, created a digital twin of the telescope to monitor its complex deployment in space and to help troubleshoot any problems that might arise. The digital twin updates itself daily with 800 million data points and is used to train operators, predict the effects of software updates, and troubleshoot issues. The concept of digital twins was first introduced by Michael Grieves in 2002, and the term was popularized by NASA employee John Vickers in 2010. As technology has advanced, digital twins have become more common in both the defense and scientific industries, with the space industry being a particular area where the two sectors converge. The JWST's digital twin is just one example of how these twins are helping scientists run the world's most complex instruments and revealing more about the world and the universe beyond.
  5. With the addition of profiling to OpenTelemetry, we expect continuous production profiling to hit the mainstream.
  6. This article explains the differences between observability, telemetry, and monitoring, and how they work together to help teams understand and improve their software systems. It also discusses the benefits of using OpenTelemetry, a standard for creating and collecting telemetry for software systems, and Honeycomb's observability platform.
  7. SIEM market is undergoing significant changes, with many vendors included in Gartner's latest Magic Quadrant report. However, amid the cloud transformation, vendor consolidation, and competition and integration with extended detection and response (XDR), the future is uncertain. The recent acquisition of Splunk by Cisco and IBM selling its QRadar software-as-a-service (SaaS) assets to Palo Alto Networks indicate that some big players are shifting strategies. Gartner Distinguished VP Analyst Peter Firstbrook suggests that IBM is giving up on SIEM and SOAR markets in favor of XDR, while Cisco is trying to figure out how to integrate Splunk with its XDR strategy. Many existing SIEM vendors will either be acquired, shift toward niche markets, or go out of business. Over the next 10 years, the SIEM market will transition to a few dominant players offering integrated platforms supplemented by specialized partner solutions.
    2024-05-26 Tags: , , , , , , by klotz
  8. New Relic's Nic Benders discusses the importance of the Innovation Centre in Hyderabad, their vision for AI, the benefits of their technologies for Indian digital businesses, and more.
  9. Honeycomb introduces a new tool, Honeycomb for Frontend Observability, to enhance web application performance. The tool integrates OpenTelemetry instrumentation as an NPM package to collect and analyze Core Web Vitals data, offering actionable insights to improve SEO and site performance.
  10. OpenTelemetry offers a standardized process for observability, but its functionality is a work in progress. Its usefulness depends on the observability tools and platforms used in conjunction with OpenTelemetry.

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