Best Observability Tools for Amazon Web Services (AWS) - Page 2

Bigeye is the data observability platform that helps teams measure, improve, and communicate data quality clearly at any scale. Every time a data quality issue causes an outage, the business loses trust in the data. Bigeye helps rebuild trust, starting with monitoring. Find missing and busted reporting data before executives see it in a dashboard. Get warned about issues in training data before models get retrained on it. Fix that uncomfortable feeling that most of the data is mostly right, most of the time. Pipeline job statuses don't tell the whole story. The best way to ensure data is fit for use, is to monitor the actual data. Tracking dataset-level freshness ensures pipelines are running on schedule, even when ETL orchestrators go down. Find out about changes to event names, region codes, product types, and other categorical data. Detect drops or spikes in row counts, nulls, and blank values to ensure everything is populating as expected.

HTCD is a cloud security SaaS built AI-first to materially upgrade your security posture. Access centralized visibility across your AWS and Azure environments—with 500+ OOTB policies for cloud security, infrastructure, network, SaaS, and compliance. All while retaining 100% ownership of your data. Create no-code detections in minutes. AI converts your questions to code for rapid results: Which CVEs can be exploited in my Azure environment? Show me S3 costs over the last 2 weeks ... and more. Get a prioritized view of security misconfigurations and vulnerabilities—solve the most pressing issues to reduce operational risk. AI reduces your response time by prioritizing in minutes what otherwise takes weeks. Get started in 15 minutes, free for 6 months for startups.

SolarWinds Observability Self-Hosted (formerly known as Hybrid Cloud Observability) is a comprehensive, integrated, full-stack observability solution designed to help organizations ensure availability and reduce remediation time across on-premises and multi-cloud environments by increasing visibility, intelligence, and productivity. It integrates data from across the IT ecosystem, including networks, servers, applications, databases, and more, providing a unified view of service delivery and component dependencies. The platform offers features such as network performance monitoring, flow monitoring and analysis, network device configuration management, IP address monitoring, and management, user and device tracking, server and application management, virtualization monitoring and management, log monitoring and analysis, server configuration management, and VoIP and network quality assurance.

Monitor your data health and pipeline performance. Gain unified visibility for pipelines running on cloud-native tools like Apache Airflow, Apache Spark, Snowflake, BigQuery, and Kubernetes. An observability platform purpose built for Data Engineers. Data engineering is only getting more challenging as demands from business stakeholders grow. Databand can help you catch up. More pipelines, more complexity. Data engineers are working with more complex infrastructure than ever and pushing higher speeds of release. It’s harder to understand why a process has failed, why it’s running late, and how changes affect the quality of data outputs. Data consumers are frustrated with inconsistent results, model performance, and delays in data delivery. Not knowing exactly what data is being delivered, or precisely where failures are coming from, leads to persistent lack of trust. Pipeline logs, errors, and data quality metrics are captured and stored in independent, isolated systems.

Acceldata is an Agentic Data Management company helping enterprises manage complex data systems with AI-powered automation. Its unified platform brings together data quality, governance, lineage, and infrastructure monitoring to deliver trusted, actionable insights across the business. Acceldata’s Agentic Data Management platform uses intelligent AI agents to detect, understand, and resolve data issues in real time. Designed for modern data environments, it replaces fragmented tools with a self-learning system that ensures data is accurate, governed, and ready for AI and analytics.

Designed for any developer or SRE, Akita delivers observability without the complexity. No code changes. No frameworks. Just deploy, observe, and learn. Solve issues quicker and ship faster. Akita helps you identify the cause of issues by modeling API behavior and mapping out how services are interacting with each other. Akita builds models of your API endpoints and their behavior, allowing you to discover breaking changes faster. Akita helps you debug latency issues and errors by showing you what has changed within your service graph. See what services you have in your system, without having to onboard service-by-service. Akita works by passively watching API traffic, making it possible to run Akita easily across your services, without changing code or using a proxy.

Visualize your microservices end-to-end, from your CDN all the way to your databases, including external dependencies. Automatically measure baselines and get recommendations of SLIs and SLOs. Understand and measure the impact across microservices. Every change introduces a ripple through your connected system. Did a security group change affect Login API? Last9 makes it easy to locate the ‘last change’ that triggered an incident. Last9 is a modern reliability stack. It’s designed to leverage your existing observability tricks and allow you to build and enforce mental models on top of your data to help you cover infrastructure, service, and product metrics with minimal effort and distractions. With all the love and passion for reliability, we address the challenges of every layer to make running systems at scale fun and embarrassingly easy! Last9 leverages the knowledge graph to automatically generate a map view of known infrastructure and service components.

Isovalent Cilium Enterprise enables cloud-native networking, security, and observability. Your cloud-native infrastructure, powered by eBPF. Connect, secure, and observe cloud-native applications in multi-cluster, multi-cloud environments. A highly scalable CNI and a multi-cluster networking solution that offers high-performance load balancing, advanced network policy management, etc. Shifting security to a process behavior instead of packet header enabling. Open source is at the core of Isovalent. We think, innovate, and breathe open source and are fully committed to the principles and values of open source communities. Request a personalized live demo with an Isovalent Cilium Enterprise expert. Engage with the Isovalent sales team to assess an enterprise-grade deployment of Cilium. Step through our interactive labs in a sandbox environment. Advanced application monitoring. Runtime security, transparent encryption, compliance monitoring, and CI/CD & GitOps integration.

​Amazon Managed Grafana is a fully managed service that simplifies the process of visualizing and analyzing operational data at scale. It allows users to create workspaces, logically isolated Grafana servers, that can be provisioned, set up, scaled and maintained automatically. These workspaces enable the visualization, analysis, and correlation of operational data across multiple sources, including AWS services like Amazon CloudWatch, AWS X-Ray, and Amazon Managed Service for Prometheus, as well as third-party data sources. It integrates seamlessly with AWS security services, ensuring compliance with corporate security requirements. Additionally, Amazon Managed Grafana supports migration from self-managed Grafana environments, allowing users to retain existing dashboards and configurations. It also offers collaborative features such as real-time dashboard viewing and editing, version tracking, and sharing capabilities, enhancing team productivity. ​

​Observo AI is an AI-native data pipeline platform designed to address the challenges of managing vast amounts of telemetry data in security and DevOps operations. By leveraging machine learning and agentic AI, Observo AI automates data optimization, enabling enterprises to process AI-generated data more efficiently, securely, and cost-effectively. It reduces data processing costs by over 50% and accelerates incident response times by more than 40%. Observo AI's features include intelligent data deduplication and compression, real-time anomaly detection, and dynamic data routing to appropriate storage or analysis tools. It also enriches data streams with contextual information to enhance threat detection accuracy while minimizing false positives. Observo AI offers a searchable cloud data lake for efficient data storage and retrieval.

DataBahn.ai is redefining how enterprises manage the explosion of security and operational data in the AI era. Our AI-powered data pipeline and fabric platform helps organizations securely collect, enrich, orchestrate, and optimize enterprise data—including security, application, observability, and IoT/OT telemetry—for analytics, automation, and AI. With native support for over 400 integrations and built-in enrichment capabilities, DataBahn streamlines fragmented data workflows and reduces SIEM and infrastructure costs from day one. The platform requires no specialist training, enabling security and IT teams to extract insights in real time and adapt quickly to new demands. We've helped Fortune 500 and Global 2000 companies reduce data processing costs by over 50% and automate more than 80% of their data engineering workloads.

The only real-time, analytics-driven multicloud monitoring solution for all environments (formerly SignalFx). Monitor any environment on a massively scalable streaming architecture. Open, flexible data collection and rapid visualizations of services in seconds. Purpose built for ephemeral and dynamic cloud-native environments at any scale (e.g., Kubernetes, container, serverless). Detect, visualize and resolve issues as soon as they arise. Monitor infrastructure performance in real-time at cloud scale through predictive streaming analytics. Over 200 pre-built integrations for cloud services and out-of-the-box dashboards for rapid visualization of your entire stack. Autodiscover, breakdown, group, and explore clouds, services and systems. Quickly and easily understand how your infrastructure behaves across different services, availability zones, Kubernetes clusters and more.

StackState's Topology and Relationship-Based Observability platform lets you manage your dynamic IT environment more effectively by unifying performance data from your existing monitoring tools into a single topology. Enabling you to: 1. 80% Decreased MTTR: by identifying the root cause and alerting the right teams with the correct information. 2. 65% Fewer Outages: through real-time unified observability and more planful planning. 3. 3x Faster Releases: by giving time back to developers to increase implementations. Get started today with our free guided demo: https://www.stackstate.com/schedule-a-demo

AppScope is a new approach to black-box instrumentation delivering ubiquitous, unified telemetry from any Linux executable by simply prepending scope to the command. Talk to any customer using Application Performance Management, and they’ll tell you how much they love their solution, but they wish they could extend it to more of their applications. Most have 10% or fewer of their apps instrumented for APM, and are supplementing what they can with basic metrics. Where does this leave the other 80%? Enter AppScope. No language-specific instrumentation. No application developers required. AppScope is language agnostic and completely userland; works with any application; scales from the CLI to production. Send AppScope data to any existing monitoring tool, time series database, or log tool. AppScope allows SREs and Ops teams to interrogate running applications to discover how they work and their behavior in any deployment context, from on-prem to cloud to containers.

Cilium is open-source software for providing, securing and observing network connectivity between container workloads, cloud native, and fueled by the revolutionary Kernel technology eBPF. Kubernetes doesn't come with an implementation of Load Balancing. This is usually left as an exercise for your cloud provider or in private cloud environments an exercise for your networking team. Cilium can attract this traffic with BGP and accelerate leveraging XDP and eBPF. Together these technologies provide a very robust and secure implementation of load balancing. Cilium and eBPF operate at the kernel layer. With this level of context, we can make intelligent decisions about how to connect different workloads whether on the same node or between clusters. With eBPF and XDP Cilium enables significant improvements in latency and performance and eliminates the need for Kube-proxy entirely.

DX Unified Infrastructure Management is the only solution that provides an open architecture, full-stack observability, and zero-touch configuration for monitoring traditional data center, public cloud, and hybrid infrastructure environments. Designed to ensure an optimal end-user experience, this solution provides a modern HTML5 operations console that makes it easy and fast for today’s IT teams to implement, use, and scale, leading to faster time to value. DX Unified Infrastructure Management provides actionable insights for cloud environments, such as AWS and Azure, and the modern architectures associated with cloud services, such as Nutanix, Hadoop, Mongo, Apache, etc. It combines deep domain knowledge across hybrid cloud infrastructure elements to help drive digital transformation, automation, and innovation. Automatically discover devices based on properties, then automatically set policies for each device type and deploy configurations and alarm policies as needed.

CtrlStack manages a wide variety of operational activities and sources of changes to reduce risks, track change impact, and find root causes of production issues fast. Relationship mapping in observability is finding meaningful connections and interactions between the data – metrics, events, logs, and traces. We use a native graph database to represent this “data between the data” at speed and scale. Get an end-to-end visibility of all changes across commits, configuration files, and feature flags in one click. Capture all the context of an incident at the moment it occurs, and at any time during diagnosis and resolution, to avoid reverting each other’s changes. Get insights into what, when, and who made the change, and how it impacts operations. Collaborate across teams with shared data knowledge through a DevOps graph.