EraSearch Integrations

Grafana Labs delivers the leading AI-powered observability platform, built around Grafana—the most widely adopted open source technology for dashboards and visualization. Recognized as a Leader in the 2025 Gartner® Magic Quadrant™ for Observability Platforms, Grafana Labs supports more than 25 million users and thousands of organizations worldwide, from startups to Fortune 500 enterprises. Grafana Cloud is the open observability cloud, designed to help engineering teams observe everything and solve anything. Built on open source, open standards, and open ecosystems, it unifies metrics, logs, traces, and profiles in a single platform for full-stack visibility across applications, infrastructure, and digital experiences. At the core is the open-source LGTM stack: Grafana for dashboards and visualization, Mimir for metrics, Loki for logs, and Tempo for distributed tracing. Native OpenTelemetry and Prometheus support allow teams to ingest telemetry from virtually any environment, while hundreds of integrations connect existing tools and data sources without costly rip-and-replace migrations. Grafana Cloud combines powerful analytics with AI-driven observability. Grafana Assistant helps engineers investigate issues, explore telemetry, and troubleshoot faster. Adaptive Telemetry identifies the data that matters most and aggregates the rest, helping organizations reduce telemetry costs while preserving valuable insights . With solutions for Kubernetes monitoring, application observability, digital experience monitoring, incident response, synthetic monitoring, and performance testing, Grafana Cloud delivers a complete observability platform that scales with your business.

Amazon CloudWatch serves as a comprehensive monitoring and observability tool designed specifically for DevOps professionals, software developers, site reliability engineers, and IT administrators. This service equips users with essential data and actionable insights necessary for overseeing applications, reacting to performance shifts across systems, enhancing resource efficiency, and gaining an integrated perspective on operational health. By gathering monitoring and operational information in the forms of logs, metrics, and events, CloudWatch delivers a cohesive view of AWS resources, applications, and services, including those deployed on-premises. Users can leverage CloudWatch to identify unusual patterns within their environments, establish alerts, visualize logs alongside metrics, automate responses, troubleshoot problems, and unearth insights that contribute to application stability. Additionally, CloudWatch alarms continuously monitor your specified metric values against established thresholds or those generated through machine learning models to effectively spot any anomalous activities. This functionality ensures that users can maintain optimal performance and reliability across their systems.

Apache Kafka® is a robust, open-source platform designed for distributed streaming. It can scale production environments to accommodate up to a thousand brokers, handling trillions of messages daily and managing petabytes of data with hundreds of thousands of partitions. The system allows for elastic growth and reduction of both storage and processing capabilities. Furthermore, it enables efficient cluster expansion across availability zones or facilitates the interconnection of distinct clusters across various geographic locations. Users can process event streams through features such as joins, aggregations, filters, transformations, and more, all while utilizing event-time and exactly-once processing guarantees. Kafka's built-in Connect interface seamlessly integrates with a wide range of event sources and sinks, including Postgres, JMS, Elasticsearch, AWS S3, among others. Additionally, developers can read, write, and manipulate event streams using a diverse selection of programming languages, enhancing the platform's versatility and accessibility. This extensive support for various integrations and programming environments makes Kafka a powerful tool for modern data architectures.

Telegraf is an open-source server agent that helps you collect metrics from your sensors, stacks, and systems. Telegraf is a plugin-driven agent that collects and sends metrics and events from systems, databases, and IoT sensors. Telegraf is written in Go. It compiles to a single binary and has no external dependencies. It also requires very little memory. Telegraf can gather metrics from a wide variety of inputs and then write them into a wide range of outputs. It can be easily extended by being plugin-driven for both the collection and output data. It is written in Go and can be run on any system without external dependencies. It is easy to collect metrics from your endpoints with the 300+ plugins that have been created by data experts in the community.

Centralize, transform, and store your data seamlessly. Logstash serves as a free and open-source data processing pipeline on the server side, capable of ingesting data from numerous sources, transforming it, and then directing it to your preferred storage solution. It efficiently handles the ingestion, transformation, and delivery of data, accommodating various formats and levels of complexity. Utilize grok to extract structure from unstructured data, interpret geographic coordinates from IP addresses, and manage sensitive information by anonymizing or excluding specific fields to simplify processing. Data is frequently dispersed across multiple systems and formats, creating silos that can hinder analysis. Logstash accommodates a wide range of inputs, enabling the simultaneous collection of events from diverse and common sources. Effortlessly collect data from logs, metrics, web applications, data repositories, and a variety of AWS services, all in a continuous streaming manner. With its robust capabilities, Logstash empowers organizations to unify their data landscape effectively. For further information, you can download it here: https://sourceforge.net/projects/logstash.mirror/

Kibana serves as a free and open user interface that enables the visualization of your Elasticsearch data while providing navigational capabilities within the Elastic Stack. You can monitor query loads or gain insights into how requests traverse your applications. This platform offers flexibility in how you choose to represent your data. With its dynamic visualizations, you can start with a single inquiry and discover new insights along the way. Kibana comes equipped with essential visual tools such as histograms, line graphs, pie charts, and sunbursts, among others. Additionally, it allows you to conduct searches across all your documents seamlessly. Utilize Elastic Maps to delve into geographic data or exercise creativity by visualizing custom layers and vector shapes. You can also conduct sophisticated time series analyses on your Elasticsearch data using our specially designed time series user interfaces. Furthermore, articulate queries, transformations, and visual representations with intuitive and powerful expressions that are easy to master. By employing these features, you can uncover deeper insights into your data, enhancing your overall analytical capabilities.

EraDB is an innovative database architecture that emphasizes the separation of storage and computing, offers true zero-schema data storage, and incorporates machine learning for adaptable indexing, enabling users to minimize data size, cost, and complexity while ensuring rapid queries over extensive datasets. With automatic indexing on all dimensions, you don't need to determine your query requirements in advance, while its schemaless nature allows for the storage of data with varying structures. Designed for adaptability, EraDB allows for interchangeable front-end and back-end systems, catering to diverse user needs. In contrast to traditional storage engines that struggle with complex data, leading to crashes or significant slowdowns, EraDB ensures efficient handling of intricate datasets without compromising performance. This makes it a robust solution for modern data management challenges.