
ChainMemory
Agentmemory
OpenMemory MCP
Pinecone
Memo.ai
Memori
cognee
MemoryLake
Prometheus
Grafana
Datadog
NewRelic
Zabbix
Splunk
Kubernetes
Dynatrace
ChainMemory gives your AI agents persistent memory that belongs to YOU โ not to a single vendor.
Save a memory in ChatGPT, recall it in Claude or Gemini. Available via Chrome extension, MCP server (npm), or REST API. Every memory gets a cryptographic fingerprint and project states are anchored with Merkle proofs, so anyone can independently verify integrity โ no trust required.
Memories consolidate into a structured Project Brain (decisions, milestones, risks) instead of a pile of raw notes. Multi-agent native: Claude, Cursor and GPT share one consolidated state. Free tier available.
ChainMemory
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Based on our record, Prometheus seems to be more popular. It has been mentiond 300 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Prometheus scrapes metrics from the stack. Node exporter covers the host, cAdvisor covers containers, and individual services expose their own endpoints where supported. The main value isn't dashboards (though those exist) - it's having a queryable record of system state over time, and a place to hook alerts when something drifts. - Source: dev.to / 26 days ago
Prometheus is the industry-standard time-series database for infrastructure metrics. Paired with Grafana for visualization and Alertmanager for routing, it forms the backbone of monitoring at companies from startups to Netflix-scale deployments. This isn't a single tool โ it's an ecosystem. - Source: dev.to / about 1 month ago
To monitor and analyze rate limiting metrics, we're using a combination of Redis and Prometheus. We're storing rate limiting metrics in Redis and then using Prometheus to scrape the metrics and display them in a dashboard. Here's an example of how we're storing rate limiting metrics in Redis:. - Source: dev.to / about 1 month ago
In this post, we compare two forecasting models, Chronos (ChronosโBolt) and Toto, on telemetry from Prometheus and OpenSearch. We judge them with two easy metrics: MASE for point accuracy and CRPS for the quality of uncertainty. - Source: dev.to / about 2 months ago
For monitoring infrastructure, Prometheus and Grafana are widely used for pipeline metrics collection and alerting. For orchestration that includes built-in run observability, Apache Airflow tracks run history, task durations, and failure states in a web UI. Python with SQLAlchemy is the standard stack for custom pipeline implementation with relational state management. - Source: dev.to / 3 months ago
Agentmemory - Persistent memory for Claude Code, Codex & coding agents
Grafana - Data visualization & Monitoring with support for Graphite, InfluxDB, Prometheus, Elasticsearch and many more databases
OpenMemory MCP - Your private, local memory layer for all AI tools
Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.
Pinecone - Search through billions of items for similar matches to any object, in milliseconds. Itโs the next generation of search, an API call away.
NewRelic - New Relic is a Software Analytics company that makes sense of billions of metrics across millions of apps. We help the people who build modern software understand the stories their data is trying to tell them.