ChaosSearch's Chaos LakeDB helps organizations make better use of their log and event data. The cloud data platform enables users to search, analyze, and visualize application telemetry data stored in Amazon S3 or Google Cloud Platform. Use cases include application observability, security analytics, product data analysis, and embedded analytics.
Our Chaos LakeDB is the first and only data lake database designed to power live Search, SQL, and Generative Artificial Intelligence (GenAI) analytics. By integrating with Amazon Web Services’ (AWS) Amazon Simple Storage Service (Amazon S3), the preferred object store for millions of AWS customers of all sizes and industries, ChaosSearch helps merge the vast storage capabilities of data lakes with the accessibility of cloud databases. Eliminating the need for complex extract, transform, load (ETL) and extract, load, transform (ELT) processes, we offer live analytics while ensuring enhanced cost efficiency and performance at scale.
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ChaosSearch is an ideal replacement for Elasticsearch (ELK stack) or Opensearch. With ChaosSearch, customers can perform scalable log analytics on AWS S3 or GCS, using familiar APIs for queries, and Kibana for log analytics and visualizations, while reducing costs and improving analytical capabilities.
ChaosSearch helps customers centralize logs to extend retention and reduce their Datadog budget in one of two ways - Use only Datadog's monitoring tools, alongside ChaosSearch for centralized log management. Or, reduce Datadog’s log retention to three days and use ChaosSearch for unlimited retention, with a cost savings of approximately 40%.
ChaosSearch reduces security and observability costs for modern enterprises, replacing Splunk for long-term analysis. Customers can keep Splunk for key security workflows and centralize all other logs in ChaosSearch – achieving 50-80% savings with unlimited, long-term data retention.
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Our Chaos LakeDB is the first and only data lake database designed to power live Search, SQL, and Generative Artificial Intelligence (GenAI) analytics. By integrating with Amazon Web Services’ (AWS) Amazon Simple Storage Service (Amazon S3), the preferred object store for millions of AWS customers of all sizes and industries, ChaosSearch helps merge the vast storage capabilities of data lakes with the accessibility of cloud databases. Eliminating the need for complex extract, transform, load (ETL) and extract, load, transform (ELT) processes, we offer live analytics while ensuring enhanced cost efficiency and performance at scale.
CHAOSSEARCH's answer
Reduced Time, Cost & Complexity
Unlimited retention without rehydration needs
Unmatched Cost-Performance at Scale
Data only in cloud storage
Chaos Index® is 5-20x smaller than raw
Small data = Small compute
Stateless = Compute just for ingest & query, not store
Unified Live Search+ SQL+GenAI Analytics
Single platform across operational & business use cases
All data stored in customers' cloud storage with granular RBAC
No sharding, partitioning, schema management including of nested data
Auto-scaling & seamless upgrades
ChaosSearch is an ideal replacement for Elasticsearch (ELK stack) or Opensearch. With ChaosSearch, customers can perform scalable log analytics on AWS S3 or GCS, using familiar APIs for queries, and Kibana for log analytics and visualizations, while reducing costs and improving analytical capabilities.
ChaosSearch helps customers centralize logs to extend retention and reduce their Datadog budget in one of two ways - Use only Datadog's monitoring tools, alongside ChaosSearch for centralized log management. Or, reduce Datadog’s log retention to three days and use ChaosSearch for unlimited retention, with a cost savings of approximately 40%.
ChaosSearch reduces security and observability costs for modern enterprises, replacing Splunk for long-term analysis. Customers can keep Splunk for key security workflows and centralize all other logs in ChaosSearch – achieving 50-80% savings with unlimited, long-term data retention.
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Tip: You can use tools like DataDog, perf (Linux), New Relic etc. To monitor cache performance. - Source: dev.to / 22 days ago
Using APM tools like NewRelic, Sentry, Datadog, etc to monitor the performance of your application and while you're on it, they can help you identify N+1 queries. - Source: dev.to / about 1 month ago
These tools track server and underlying infrastructure and backend performance. They monitor several metrics, like disk I/O, CPU and memory usage, network traffic, and more. Some examples of these tools include New Relic, Datadog, and AppDynamics. Web administrators can use them to see what's causing slow SRT, like high CPU usage or network traffic. Server-side monitoring tools also provide real-time alerts to... - Source: dev.to / 2 months ago
11 Application performance: Before we even perform a deployment, we should configure monitoring tools like Retrace, DataDog, New Relic, or AppDynamics to look for performance problems, hidden errors, and other issues. During and after the deployment, we should also look for any changes in overall application performance and establish some benchmarks to know when things deviate from the norm. - Source: dev.to / 2 months ago
Recently, we have been experiencing some Latency issues. The reason being the increase in our userbase as more companies are adopting our platform to do their procurement efficiently. Our core product is a monolith rails application served on AWS servers. We use AWS ELB's Application load balancer to swiftly balance the load on multiple servers and increase them when needed. So, these sudden latency issues caused... - Source: dev.to / 2 months ago
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