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The latest News and Information on Log Management, Log Analytics and related technologies.

Transform your public sector organization with embedded GenAI from Elastic on AWS

Elastic featured in AWS Generative AI Hub for public sector Elastic is proud to be featured in the new AWS Generative AI Content Hub for public sector — a destination showcasing the most impactful ways agencies can securely adopt and scale generative AI (GenAI).

What Are Vector Embeddings? (Explained in 2 Minutes)

In under 2 minutes, we explain what vector embeddings are, how they work, and how to use them in real-world applications like text expansion. We'll also show how Elasticsearch supports vector search with two powerful models: E5, open-source text embedding models designed for multilingual search, and ELSER, a sparse embeddings model from Elastic.

The Fourth Pillar of Observability

Your application is only as reliable as the infrastructure it runs on. Most commonly, that means Kubernetes is doing the job by managing fleets of containers, scaling services on demand, and keeping workloads distributed across nodes. Traditional dashboards weren’t built to scale with this reality. They give you snapshots of raw metrics. They don’t scale to multi-cluster environments. They don’t map relationships between resources.

Logs are Generally Available (Still logs, just finally useful)

When we started building Logs in Sentry we had one goal: make them useful for real debugging, not just another high-volume text storage. This meant making them "trace connected" from day one. This let us ensure they were tightly connected to the actions and performance happening in your application, right where developers already go to investigate errors, performance, and latency issues. Now, Logs is out of beta and generally available to everyone.

Visualize Logs Alongside Metrics: Complete Observability for Slow MongoDB Operations

MongoDB’s strength of flexible schema and fast iteration can also hide costly queries until they surface as user-facing latency, replica lag, or spiky CPU. A handful of slow operations can impact the cache, starve other workloads, and cascade into timeouts across services. Monitoring slow queries gives you an early warning system for index gaps and query-plan regressions introduced by code deploys, schema changes, or shifting data shapes.

The Debugging Bottleneck: A Manual Log-Sifting Expedition

Imagine a developer at a fast-growing company. A customer support agent reports a critical issue: a user's recent order is stuck in a "pending" state. The agent provides a customer ID and a request ID. The developer's typical process is a familiar, painful dance: This process is slow, tedious, and prone to human error. The Mean Time to Resolution (MTTR) is measured in hours, not minutes, and it's a huge drain on engineering resources.
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How to Reduce Continuous Monitoring Costs

Continuous monitoring is a crucial practice in the fields of DevOps, cybersecurity, and compliance. It involves the proactive and ongoing process of observing, assessing, and collecting data from various systems, applications, and infrastructure components in real-time or near real-time. Continuous monitoring is closely related to observability, which goes beyond simple monitoring to provide a deep understanding of complex and dynamic systems.