Datadog Log Management Extends Cloud-Scale Monitoring
Simplification — working smarter, not harder — is the driving force behind advances in technology. Everyone is looking for ways to make the things they do, and the processes they go through each day a little bit easier. When there are several different monitoring dashboards an IT manager needs to view in order to get an entire network picture, it can be time-consuming and certainly inefficient.
Gartner certainly agrees, as their Market Guide for IT Infrastructure Monitoring Tools stated that “Most organizations have five or more tools monitoring their IT infrastructure. There is a growing interest in a single dashboard that unifies data from all monitoring tools.”
Datadog, a monitoring service for hybrid cloud applications, is seeking to fill that void with newly launched Log Management capabilities. The company claims that with this new service, customers can now enrich, monitor, and analyze logs from all their systems for troubleshooting, auditing, visualization, and alerting. This addition also brings the other “pillars of observability“-metrics, tracing and logs-together in one dashboard to help try and simplify IT management.
Some features of the service include:
- Unified Dashboard – Regardless of the source, Datadog automatically collects and tags data from several different tools, platforms, and services. With this automatic correlation and grouping of data, the Datadog user interface allows you to move seamlessly between related sources of monitoring data without switching tools.
- Open-ended integrations – Once you set up an integration to send logs, Datadog automatically incorporates key attributes about your logs as facets, which allow you to search, filter, and aggregate your data. Currently, the list of possible integrations include technologies such as Apache, NGINX, Docker, HAProxy, MySQL, PostgreSQL, MongoDB, Varnish, Java, Python, C#, Node.js, Ruby, Go, AWS CloudTrail, AWS ELB, AWS ALB, AWS RDS, AWS SNS, and AWS Lambda.
- Log management pipelines – On the Pipelines page, you can apply filters, then define a series of processing steps that extract meaningful information or attributes from semi-structured text. Those attributes can then be used to filter or aggregate your data for visualization, alerting, and faceted search.
- Create alerts on data – You can also build alerts that evaluate the contents of your logs—so you can get notified whenever a particular exception occurs in unacceptable numbers, or when the number of suspicious login attempts suddenly spikes. These alerts can be configured to notify individuals or teams via services like Slack, PagerDuty, or OpsGenie, or you can create tickets in workflow systems like JIRA or ServiceNow.
Service providers can test a free 14-day trial. The cost for the log management starts at $1.27 per million log events ingested after the trial period has ended.
Datadog’s Log Management offering complements the company’s existing cloud-scale application performance monitoring (APM) and infrastructure monitoring services. Potential competitors include Cisco AppDynamics, New Relic, Dynatrace, BMC and CA Technologies, among others.
Datadog Senior VP of Alliances John Gray is building out the company’s partner program, which includes a growing number of MSPs. Gray described the partner strategy in this podcast with ChannelE2E and CompTIA.
Moreover, the company is set to launch its inaugural partner and customer conference — Datadog Dash — this July in New York.
Additional insights from Joe Panettieri.