Why
Elastic observability
Monitoring solutions have been around for a while, but the evolution in the IT environment of organizations and businesses provides new challenges. Continuous integration and deployment (CI/CD), Microservices, containers, orchestration, cloud, and serverless, … make the efficient monitoring of your logs, metrics, and traces more complex than ever before.
Elastic Observability gathers all this data in 1 single solution and empôwers it with AI and Machine Learning. By uniting data from applications, and infrastructure but just as well the business, and operational data, you can create the right insights to anticipate, and resolve issues faster and reduce your ‘mean time to resolve’ (MTTR).
benefits of
elastic observability
INTEGRATIons
Elastic offers countless out-of-the-box integrations with source systems and applications, whether it’s on the cloud, on-premise, or in hybrid environments. Data ingestion is often complex, but not with Elastic’s turn-key connectors.
PAY-AS-YOU-USE
Elastic understood that a straightforward pricing model is greatly appreciated. No hassle with ingest- or agent-based pricing models that prevent organizations to capture all data to their monitoring system. You just pay for the resources you use to run your Elastic platform. No matter the use case. On top of that, you receive plenty of extra functionalities like index lifecycle management to optimize the use of these resources.
ELIMINate SILOS
Monitor your logs, infrastructure metrics, and stack traces. With APM – Application Performance Monitoring – you receive an out-of-the-box dashboard that correlates all data for a thorough analysis to identify deviations faster. Focus yourself on the interactions your end-users have with your web applications and gain insights into what works, and what doesn’t.
MACHINE LEARNING
Because of the strong digitalization, a modern IT infrastructure is, just like the business end, active 24/7. Maintenance or keep-it-running activities encompass the bulk of most IT budgets. Organizations switched ‘en masse’ to agile and DevOps to develop applications faster & better. So, no time to lose when talking about root cause analysis and the tracking of issues.
Intelligent alerting capabilities and machine learning-based anomaly detection will help Ops teams to separate what’s important. Thanks to rich analysis and visualization options, problems can be detected faster which will reduce costs.
FUTURE-PROOF
Organizations are placing their workloads in cloud environments which in turn creates hybrid and multi-cloud infrastructures. Elastic offers seamless data streams from distributed environments.
A flexible deployment model offers you the choice of on-premise, private or public cloud, Elastic cloud is available on Amazon Web Services, Google Cloud, and Microsoft Azure. Scaling your Elastic platform is as simple as adding nodes to your cluster.
AI assistant
Elastic AI Assistant is a generative AI powered by the Elasticsearch Relevance Engine™ (ESRE).
The AI Assistant aims to redefine how Site Reliability Engineers (SREs) identify & resolve problems, eliminating manual data hunting.
who needs elastic observability
Elastic has been recognized as a visionary in the 2022 Gartner Magic Quadrant voor APM en Observability.
Performance & reliability of systems and applications are tremendously important. We see at our customers there is plenty to gain on operations in efficiency. Analyzing end-user, infrastructure- and application monitoring data within the same platform easily deals with blind spots which will lead to reducing your MTTD and MTTR.
Machine learning and integration with incident management workflows automate service management operations. Elastic has domain-specific and scalable models and jobs on board, as well as supervised and unsupervised machine learning.
Data is all around us and is being used in all ways possible to give enterprises an advantage over their competitors. Next to operational use cases, we see that our customers also resort to Elasticfor data platform use cases.
The Elastic Stack offers the option to load any data, even your unique datasets. This means Elastic can be used to improve customer experiences, detect fraud, and even predict customer journeys.