The latest News and Information on Observabilty for complex systems and related technologies.
Code instrumentation is an essential practice in modern software development. Not only does it aid in debugging, it ultimately impacts the MTTR (Mean Time to Resolve) for software running in production. With changing software architectures and deployment patterns over the years, approaches to code instrumentation have also undergone a significant shift.
Quickly: if you’re interested in observability for LLMs, we’d love to talk to you! And now for our regularly scheduled content: In early May, we released the first version of our new natural language querying interface, Query Assistant. We also talked a lot about the hard stuff we encountered when building and releasing this feature to all Honeycomb customers. But what we didn’t talk about was how we know how our use of an LLM is doing in production!
On June 28th I will be hosting a webinar, ‘The Fundamentals of Searching Observability Data’. So why should you attend? Because things have, and will continue to change in the way we manage the IT data collected across the enterprise. A recent study shows that enterprises create over 64 zettabytes (ZB) of data, and that number is growing at a 27 percent compound annual growth rate (CAGR). The scary part?
IT, DevOps, and security teams are figuring out the best ways to manage their complex, ever-growing, ever-changing environments. And one contributing factor to all the complexity is the rise of using multiple cloud services. One cloud service to manage is difficult enough, but adding more to the mix — each with its own interface and set of tools — makes everyone’s job significantly more difficult.
In Elasticsearch 8.8, we’re introducing the reroute processor in technical preview that makes it possible to send documents, such as logs, to different data streams, according to flexible routing rules. When using Elastic Observability, this gives you more granular control over your data with regard to retention, permissions, and processing with all the potential benefits of the data stream naming scheme. While optimized for data streams, the reroute processor also works with classic indices.
Application Programming Interfaces (APIs) are a crucial building block in modern software development, allowing applications to communicate with each other and share data consistently. APIs are used to exchange data inside and between organizations, and the widespread adoption of microservices and asynchronous patterns boosted API adoption inside the application itself.
The benefits of going cloud-native are far reaching: faster scaling, increased flexibility, and reduced infrastructure costs. According to Gartner®, “by 2027, more than 90% of global organizations will be running containerized applications in production, which is a significant increase from fewer than 40% in 2021.” Yet, while the adoption of containers and Kubernetes is growing, it comes with increased operational complexity, especially around monitoring and visibility.
Today’s IT systems are ever more fragmented. It is commonplace to see polyglot systems, written in multiple programming languages, and using a plethora of tools and cloud services as infrastructure building blocks, whether data stores, web proxy or other functions. In this dynamic cloud-native realm, open standards and open specifications have become integral drivers of compatibility, collaboration, and convergence – the Three C’s of Open Standards, if you will.
