Many of us remember the public service announcements asking parents if they knew where their kids were at night. They were ominous and a little alarming. Asking yourself the same question about your data can be equally as scary, but Cribl Edge can help.
Elasticsearch® recently released time series data streams for metrics. This not only provides better metrics support in Elastic Observability, but it also helps reduce storage costs. We discussed this in a previous blog. In this blog, we dive into how to enable and use time series data streams by reviewing what a time series metrics document is and the mapping used for enabling time series. In particular, we will showcase this by using Elastic Observability’s Nginx integration.
As someone who admittedly gets bored easily, one of my favorite things about working for a company like Cribl is the huge amount of technologies in our ecosystem I get exposure to. Over time, I also get to observe trends in the market – it’s always so cool to see big upswings in adoption for various platforms and tech. One such trend I’ve observed over the last year is a noticeable uptake and presence in the market of Google Chronicle.
The Elastic APM Java Agent automatically tracks many metrics, including those that are generated through Micrometer or the OpenTelemetry Metrics API. So if your application (or the libraries it includes) already exposes metrics from one of those APIs, installing the Elastic APM Java Agent is the only step required to capture them. You'll be able to visualize and configure thresholds, alerts, and anomaly detection — and anything else you want to use them for!
Python is a highly skilled language with a large developer community, which is essential in data science, machine learning, embedded applications, and back-end web and cloud applications. And logging is critical to understanding software behavior in Python. Once logs are in place, log monitoring can be utilized to make sense of what is happening in the software. Python includes several logging libraries that create and direct logs to their assigned targets.
Event Hubs is Microsoft’s cloud-native real-time event streaming service. For Event Hubs to work, data must be pushed to or pulled from it. That is where Cribl Stream comes in. Event Hubs is a source and destination inside Cribl Stream and the control for how you route, shape, and transform your data from Event Hubs. But, one does not simply Stream into (or from) Event Hubs. There is a lot that goes into architecting an Event Hubs Source.
Consistent performance and continuous improvement: these are the fundamentals we should aspire to in the world of cloud software delivery. We focus on ensuring our systems become more consumable, enjoyable and innovative. We seek to make customers’ lives easier and more productive through incremental achievements, and doing a better job, every day.
Psst, hey pal, would you like to buy a time machine? I am not talking about some H.G. Wells monstrosity where you somehow end up being chased by dinosaurs or become your own grandparent. But a time machine for your observability data. License costs and tool performance often keep organizations from ingesting all their data or require them to limit data retention time. Security incidents are often discovered long after these retention times are exhausted or require data that was never ingested.
A comprehensive guide to support faster drug innovation and discovery in the pharmaceutical industry with generative AI/LLMs, custom models, and the Elasticsearch Relevance Engine (ESRE) Faster drug discovery leading to promising drug candidates is the main objective of the pharmaceutical industry. To support that goal, the industry has to find better ways to utilize both public and proprietary data — at speed and in a safe way.
