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Logging

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

How To Harness the Full Potential of ELK Clusters

The ELK Stack is a collection of three open-source projects, Elasticsearch, Logstash, and Kibana. They operate together to centralize and examine logs and other types of machine-generated data in real time. With the ELK stack, you can utilize clusters for effective log and event data analysis and other uses. ELK clusters can provide significant benefits to your organization, but the configuration of these clusters can be particularly challenging, as there are a lot of aspects to consider.

Structure of Logs (Part 2) | Zero to Hero: Loki | Grafana

Have you just discovered Grafana Loki? Zero to Hero: Loki is a series of videos that aims to take you through the basics of ingesting, your logs into Grafana Loki an open-source log aggregation solution. In this episode, it's all about the structure of logs. In part 2 we cover the different ways a log can be formatted. ☁️ Grafana Cloud is the easiest way to get started with Grafana dashboards, metrics, logs, and traces. Our forever-free tier includes access to 10k metrics, 50GB logs, 50GB traces and more. We also have plans for every use case.

Why Organizations are Using Grafana + Loki to Replace Datadog for Log Analytics

Datadog is a Software-as-a-Service (SaaS) cloud monitoring solution that enables multiple observability use cases by making it easy for customers to collect, monitor, and analyze telemetry data (logs, metrics and traces), user behavior data, and metadata from hundreds of sources in a single unified platform.

Top 10 Change Management Tools

Changes to software are inevitable and fundamental part of growth for any organization, however, change is often not straightforward. It can affect numerous aspects of a company and requires collaboration among all stakeholders. This is where change management tools come in to assist you with this. There’s currently a wide range of change management tools available, each providing benefits to specific scenarios and weaknesses to others.

Control your log volumes with Datadog Observability Pipelines

Modern organizations face a challenge in handling the massive volumes of log data—often scaling to terabytes—that they generate across their environments every day. Teams rely on this data to help them identify, diagnose, and resolve issues more quickly, but how and where should they store logs to best suit this purpose? For many organizations, the immediate answer is to consolidate all logs remotely in higher-cost indexed storage to ready them for searching and analysis.

Aggregate, process, and route logs easily with Datadog Observability Pipelines

The volume of logs generated from modern environments can overwhelm teams, making it difficult to manage, process, and derive measurable value from them. As organizations seek to manage this influx of data with log management systems, SIEM providers, or storage solutions, they can inadvertently become locked into vendor ecosystems, face substantial network costs and processing fees, and run the risk of sensitive data leakage.

Dual ship logs with Datadog Observability Pipelines

Organizations often adjust their logging strategy to meet their changing observability needs for use cases such as security, auditing, log management, and long-term storage. This process involves trialing and eventually migrating to new solutions without disrupting existing workflows. However, configuring and maintaining multiple log pipelines can be complex. Enabling new solutions across your infrastructure and migrating everyone to a shared platform requires significant time and engineering effort.

Migrating from Elastic's Go APM agent to OpenTelemetry Go SDK

As we’ve already shared, Elastic is committed to helping OpenTelemetry (OTel) succeed, which means, in some cases, building distributions of language SDKs. Elastic is strategically standardizing on OTel for observability and security data collection. Additionally, Elastic is committed to working with the OTel community to become the best data collection infrastructure for the observability ecosystem.