Operations | Monitoring | ITSM | DevOps | Cloud

How to add powerful (Elastic)search to existing SQL applications

Elasticsearch has a lot of strengths (speed, scale, relevance), but one of its most important strengths is its flexibility to be added to existing environments without the need for any sort of architectural overhaul. If you are a sysadmin (dev, sec, ops, etc.), you know just how appealing this is. So many legacy systems remain in place not because they are perfect, but because replacing them would cost time and money that you don't have.

Identifying and monitoring key metrics for your hosts and systems

This post is the first in a three-part series on how to effectively monitor the hosts and systems in your ecosystem, and we're starting with the one you use most: your personal computer. Metrics are a key part of observability, providing insight into the usage of your systems, allowing you to optimize for efficiency and plan for growth. Let's take a look at the different metrics you should be monitoring.

Improving search relevance with boolean queries

When you perform a search in Elasticsearch, results are ordered so that documents which are relevant to your query are ranked highly. However, results that may be considered relevant for one application may be considered less relevant for another application. Because Elasticsearch is super flexible, it can be fine-tuned to provide the most relevant search results for your specific use case(s).

How to easily correlate logs and APM traces for better observability

Application performance monitoring (APM) and logging both provide critical insight into your ecosystem. When paired together with context, they can provide vital clues on how to resolve problems with your applications. As the log data you analyze becomes more complex, navigating to the relevant pieces can be tricky using traditional tools. With Elastic Observability (powered by the Elastic Stack), correlating logs with APM is as simple as a few clicks in Kibana.

Searching Salesforce: Boosting your teams' productivity with Elastic Workplace Search

“If it’s not in Salesforce, it didn’t happen.” You’ve undoubtedly heard it, or perhaps you’ve said it yourself. And why not? Over the past 15 years, Salesforce has redefined the CRM industry, becoming the de facto solution for managing sales, customer service, marketing automation, and analytics functions with its cloud-only approach. As Salesforce’s solutions have expanded so has their user base.

Elasticsearch Service on Google Cloud Marketplace: New ways to purchase and discover

Last year we announced an expanded partnership with Google to bring Elasticsearch Service to even more Google Cloud users. We were also named one of Google Cloud's partners of the year! We've since deepened our partnership, and today we are proud to announce new ways to purchase and discover Elasticsearch Service in the Google Cloud Marketplace. You can now purchase monthly Gold and Platinum subscriptions as well as Standard, Gold, and Platinum annual subscriptions through the marketplace.

Exploring Jaeger traces with Elastic APM

Jaeger is a popular distributed tracing project hosted by the Cloud Native Computing Foundation (CNCF). In the Elastic APM 7.6.0 release we added support for ingesting Jaeger traces directly into the Elastic Stack. Elasticsearch has long been a primary storage backend for Jaeger. Due to its fast search capabilities and horizontal scalability, Elasticsearch makes an excellent choice for storing and searching trace data, along with other observability data such as logs, metrics, and uptime data.

Elastic Cloud: Elasticsearch Service API is now GA

The Elastic Cloud console gives you a single place to create and manage your deployments, view billing information, and stay informed about new releases. It provides an easy and intuitive user interface (UI) for common management and administrative tasks. While a management UI is great, many organizations also want an API to automate common tasks and workflows, especially for managing their deployments.

How to implement Prometheus long-term storage using Elasticsearch

Prometheus plays a significant role in the observability area. An increasing number of applications use Prometheus exporters to expose performance and monitoring data, which is later scraped by a Prometheus server. However, when it comes to storage, Prometheus faces some limitations in its scalability and durability since its local storage is limited by single nodes.

Elastic Stack 7.7.0 released

We are pleased to announce the general availability of version 7.7 of the Elastic Stack. Like most Elastic Stack releases, 7.7 packs quite a punch. But more than the new features, we’re most proud of the team that delivered it. A feature-packed release like this is special during normal times. But it’s extra special today given the uncertain times we are in right now.