The latest News and Information on Log Management, Log Analytics and related technologies.
The observability landscape is constantly changing and evolving. Despite this, one question often plagues operations leaders: "How can we consolidate disparate data sources and tools to view system performance comprehensively?" These leaders have sought the answer in a single-pane-of-glass solution. However, as Jason Bloomberg and Buddy Brewer discussed in the Mezmo webinar "Solving the Single Pane of Glass Myth," this idea is more myth than reality.
With various open source platforms on the market, engineers have to make smart and cost-effective choices for their teams in order to scale. Elastic Cloud, and its flagship product Elasticsearch, are one of several options available, but how do they compare to a full-stack observability platform like Coralogix? This article will provide a complete breakdown between Coralogix and Elastic Cloud, from essential industry features, like logs, metrics and traces, to pricing models and support services.
One of the most captivating discussions I had at KubeCon Europe 2023 in Amsterdam was about standardization of a query language for observability. This query language standard aims to provide a unified way of querying observability data across logs, metrics, traces, and other relevant signals. The conversation shed light on the pressing need for a standardized approach to overcome the challenges posed by the plethora of query languages currently in use.
On July 4th we celebrate. We celebrate freedom of movement, freedom of assembly, removal of excessive taxation, and much, much more. But what about digital independence? Removing the tyrannical yoke of control over your observability data. Authoritarian vendors restrict access and movement; they dictate proprietary formatting and even limit what can be commingled with your data, then apply enormous tax burdens (i.e. license fees) just to store your data.
In this post I will introduce sysgrok, a research prototype in which we are investigating how large language models (LLMs), like OpenAI's GPT models, can be applied to problems in the domains of performance optimization, root cause analysis, and systems engineering. You can find it on GitHub.
By storing copies of your content in geographically distributed servers, content delivery networks (CDNs) enable you to extend the reach of your app without sacrificing performance. CDNs lessen the demand on individual web hosts by increasing the number and regional spread of servers that are able to respond to incoming requests for cached content. As a result, they can deliver web content faster and provide a better experience for your end users.
