Amazon CloudWatch Customers

The CloudWatch observability platform has improved our team's visibility into application performance, streamlining and speeding collaboration for our team. It delivers real-time insights into application performance and offers thorough end-to-end analytics, empowering teams to make more informed, data-driven decisions. As a result, we can more efficiently and proactively maintain and manage performance, allowing our teams to focus on innovation and excellence and helping shape a world where life just works better for our teams and customers.

Using the new integrated analytics experience and zero-ETL integration between Amazon CloudWatch and Amazon OpenSearch Service, Works Human Intelligence can create out-of-the-box OpenSearch dashboards for VPC Flow logs and CloudTrail. This helps us monitor, analyze, and troubleshoot using visualizations derived from the logs.

The integration between CloudWatch and OpenSearch service has been a game-changer for us! Our teams were already comfortable using OpenSearch Piped Processing Language (PPL) and SQL, so the learning curve for using PPL/SQL in CloudWatch Logs Insights was minimal. We’re able to troubleshoot faster, and the dashboards make it easy to spot trends and potential issues from our logs. This means less time digging through data and more time focusing on what matters.

With the new integrated analytics experience and zero-ETL integration between Amazon CloudWatch and Amazon OpenSearch Service, Yayoi no longer has to copy logs from CloudWatch for analysis, or create ETL pipelines. Now, we can use OpenSearch Discover to analyze CloudWatch logs in-place, and build indexes and dashboards on CloudWatch Logs.

Amazon CloudWatch is a key component of Zurich Insurance’s observability infrastructure. At Zurich, we are committed to maintaining observability as close to the workload as possible, and we have a strong preference for leveraging cloud-native tools whenever practical. Amazon CloudWatch not only aligns with these objectives but also enhances our capability to monitor workloads directly where they operate. By centralising our metrics and alerts, Amazon CloudWatch streamlines our issue response processes, enabling us to identify and address problems more efficiently. This centralised observability framework helps us to reduce our mean time to recovery, ensuring that we maintain the highest standards of service continuity and reliability for our customers. With Amazon CloudWatch, we can confidently oversee our infrastructure and proactively manage any potential disruptions, reinforcing Zurich Insurance’s commitment to operational excellence and customer satisfaction.

The Amazon CloudWatch team has been indispensable in our migration away from our previous observability solution, motivated by cost and usability concerns. Our transition includes using CloudWatch Synthetics for TLS certificate monitoring and API endpoint surveillance, alongside application instrumentation via OpenTelemetry (OTEL) and the PHP SDK for tracing. Crucial performance metrics like Response Time; Error Rate which is derived from Error Count and Request Count; and Transaction Count are meticulously monitored. Anomaly detection systems are in place to spot irregularities in response time and error rates. We've also integrated PagerDuty and an SNS topic for issue alerts. Our partnership with CloudWatch transcends typical customer relationships, emphasizing collaboration and their remarkable responsiveness, exemplified when they rapidly implemented tailored solutions. This underscores the extraordinary value of our partnership with AWS and the CloudWatch team.

EA Sports partnered with AWS to beta test Amazon CloudWatch Internet Monitor to help address several of EA Sports’ core priorities. One of these priorities was to reduce their mean-time-to-detect internet issues by accurately, and with confidence, identifying user drops caused by internet connectivity issues. They also wanted to detect whether application performance issues were due to internet fluctuations or the AWS network, and to understand the impact to the game stack. Finally, it was important to them to dissect specific traffic paths that ingress globally to EA games, to help them understand where and how users connect to them. Anomaly detection for user impact has typically taken a lot of time, and diagnosing issues often.

Samsung Cloud provides a smooth backup, sync, restore, and upgrade experience for all your Galaxy devices. AWS X-Ray is a very useful tool for developing new features in Samsung Cloud. Especially when developing use cases that require communication between multiple servers, X-Ray is very useful for identifying bottlenecks or issues that occur on specific servers. X-Ray can be linked with external components such as envoy proxy and Amazon DynamoDB with simple code, and the sub-segment shown on the X-Ray console has been a great help in tuning database queries. Additional information such as error content and HTTP status code can be added to the segment of X-Ray, and this information can be easily found on the console with just one trace ID. Through this, developers can quickly resolve problems and increase the stability of the service.

Amazon CloudWatch Metrics provides a rich, comprehensive set of metrics out of the box for all AWS services. What's most important to us, the SonarCloud SRE squad, however, is measuring and monitoring how our services perform from a functional standpoint, since this is what SonarCloud's users perceive. To achieve this, our application services produce functional metrics using the CloudWatch Embedded Metric Format. This essentially transforms JSON log entries into CloudWatch custom metrics data points in real-time. This is extremely simple to implement and loosely coupled with the infrastructure: all you need is logs! With this, we have a complete picture of how our application services perform and use this data to improve and react to issues.

Earlier this year we released new PGA TOUR Digital experiences giving our fans access to real-time leader boards, faster tournament updates, gaming odds, and in-depth player information on mobile and web platforms. These new experiences continuously deliver better overall fan engagement. Building on AWS gave our development team everything we needed to deliver a modern application and using CloudWatch allows us to monitor the backend of our mobile and web applications. We can utilize CloudWatch dashboards along with synthetic canaries to easily visualize and proactively monitor and alert on multiple different AWS services including AppSync and Lambda with one pane of glass. Having immediate access to system status and availability allows us to deliver the best possible experience to our fans.

Amazon CloudWatch plays a crucial role in Solaris' operations with its versatile features, particularly in logging and monitoring our metrics, logs, and traces. We gain valuable insights into our microservices architecture and applications running across all AWS accounts with CloudWatch cross-account observability. CloudWatch Logs enables us to perform efficient debugging and conduct in-depth root cause analysis, ensuring the smooth functioning of our systems, together with CloudWatch Metrics that allows us to monitor ongoing issues related to resource consumption and serve as an input for triggering alarms based on high error rates or anomalies. CloudWatch Alarms also play a pivotal role in promptly alerting us through various channels like Slack and PagerDuty, ensuring timely responses to critical situations. Moreover, CloudWatch's comprehensive capabilities empower us to proactively manage our systems, detect issues, and optimize our resources effectively.

Using Amazon CloudWatch Logs Infrequent Access, Fluent Commerce is now able to scale our business, while cost effectively supporting our customer’s needs. We love the flexibility of choosing the Standard log class for comprehensive data analytics and Infrequent Access log class for high-volume application logs. This helps us enhance application visibility, increase operational efficiency and manage costs.

Our customers are our most important assets. Amazon CloudWatch provides developers and Site Reliability Engineers real-time observability of systems and products that reduce customer impact. We collaborated across many Lines of Business testing Amazon CloudWatch features that help monitor and troubleshoot with a real-time unified view across applications and infrastructure. This has produced game-changing observability and correlation of data on metrics, logs, and traces. Data without context is meaningless and CloudWatch is helping correlate data in a contextual way making it meaningful and impactful.

With thousands of containers in use at JPMC the additional detailed metrics now offered by Amazon CloudWatch Container Insights with enhanced observability are a welcomed arsenal for faster troubleshooting as we continue to provide reliable services to our customers

As DevSecOps becomes the predominant software delivery methodology, our clients are seeking an integrated delivery model that incorporates site reliability engineering (SRE) best practices in a unified experience. Having a pre-built, integrated application and infrastructure monitoring solution utilizing cloud-native services helps our client’s monitor the performance of their applications and improve the reliability of their services. Amazon CloudWatch Application Signals addresses our client’s need for a comprehensive application monitoring solution that enables them to quickly detect, troubleshoot and resolve incidents faster, and focus on what matters most, their end users experience.

Cross-account observability in Amazon CloudWatch allows us to monitor and analyze events of all our microservices in real time from a single place, and it is integrated with AWS Organizations enabling simple configuration and management using Organizational Units. Having an AWS account for each microservice helps us develop faster and more securely. Having cross-account metrics and being able to set up critical alarms all in one place raises our observability to the next level and helps us guarantee our service level agreements and continuous improvement.

Amazon CloudWatch Container Insights helps us monitor our infrastructure and applications in real time, said Anjana Kashyap, Vice President, Engineering Services at SnapLogic. "Our customers depend on real time information for critical purposes, like financial transactions or healthcare data, Amazon CloudWatch Container Insights helps us respond to performance changes, optimize resource usage and provides us with the insights into operational health we need to keep our systems running smoothly.

Being customer focused, Thomson Reuters started to bring together different initiatives for alerts, monitoring and disaster recovery. Amazon CloudWatch brought all those together optimally with centralized logging, customized dashboards, automatic failover with health checks, and the least privileged model for critical directory services for all Thomson Reuters’ 25,000 employees. We used AWS Secrets Manager and AWS Key Management Service to improve security posture via license and database key encryptions, while Route 53 provided disaster recovery with Amazon Elastic Kubernetes Service’s self-healing and auto scaling capabilities. As a result, we accomplished all our goals with CloudWatch and related services to meet security compliance and mandated technology governance.

DesignCrowd uses CloudWatch Logs Infrequent Access to cost effectively scale and create new workloads for application instrumentation, debug and build logs while continuing to get deeper insights into the applications' health. All features available in this log class will enable our internal teams to monitor our applications without needing to limit the logs being ingested in CloudWatch.

Edge observability from Amazon CloudWatch Internet Monitor has been helpful, especially as it is customized to help us minimize false positives. Partnering with AWS will help us evolve our customized solution, and deliver consistent internet monitoring across our edge infrastructure on AWS.

Integrating AWS Container Insights with our EKS clusters was seamless, providing visibility into every layer of our Kubernetes environment, enhancing operational effectiveness, and improving our incident response capabilities.

By leveraging out of the box monitors via Amazon CloudWatch, we’ve been able to monitor our infrastructure usage via CloudWatch Metrics to identify savings opportunities on compute with ~12% savings on simple workloads and an opportunity for additional enhanced savings across more complex ones.

Tech Mahindra is looking forward to the formal release of Amazon CloudWatch Internet Monitor to add to our critical customer applications and enable intelligent root cause analysis (RCA). Our operators and service engineers were already able to perform enhanced troubleshooting using the measurements published by Internet Monitor to CloudWatch Logs in beta, helping them derive custom metrics and configure alarms to support specialized use cases for our clients. Internet Monitor can help us preempt failures due to network and infrastructure glitches, by monitoring and analyzing global AWS infrastructure health and correlating to local network latency issues that could arise.

Amazon CloudWatch Evidently has helped us identify unintended consequences before rolling out new features, and thereby helped reduce risk in our production environment. With Evidently, we can manage any vulnerabilities found in the new feature, monitor key metrics and then rollout to a wider customer base. The critical benefits Evidently provides us are the ability to split traffic between different versions and get user feedback on new features.

Cross-account observability in Amazon CloudWatch can help Tech Mahindra enable centralized monitoring for its F500 customers with a single dashboard view and unified alarms for key metrics across all accounts. Cross-account observability will alleviate challenges F500 enterprises face in managing multiple accounts and building monitoring capabilities with a consistent design across the accounts. Additionally, cross-account observability will also facilitate easy management of multiple dev and QA environments under one monitoring account, and enable a consistent way of monitoring usage and enforcing compliance. We strongly believe cross-account observability gives us opportunities to enable our customers with customized yet uniform RCA mechanisms, standardized enterprise-wide cost analysis solutions as well as application transaction monitoring and analysis.

To support our managed services operations and consulting engagements, we use Amazon CloudWatch for monitoring and logging of all AWS systems. The cross-account observability feature allows us to have a single view over all projects at a glance without any additional tools and minimal setup.

Cross account logging is a feature that our customers have been looking for, and cross-account observability in Amazon CloudWatch provides out-of-the-box integration with minimal effort. The centralized dashboard helps the support team to quickly identify and fix issues that are affecting the broader landscape. With cross-account observability in CloudWatch, there is no need for third-party tools integration for centralized logging.

Our objective at Rego SaaS is to offer white-glove service and support to our clients; we strive to identify and resolve issue before the client is impacted. CloudWatch Synthetics allows us to monitor five key metrics of our production environments. Over the past year, CloudWatch Synthetics and a simple system based on Amazon CloudWatch Alarms, Amazon SES, and AWS Lambda functions have proactively allowed us to respond to our customer's application and infrastructure issues. With CloudWatch Synthetics, our DevOps and support teams have been able begin analyzing and resolving problems even before the client notifies us of the issue. CloudWatch Synthetics is a critical component of exceeding SLAs/SLOs for our customers and, ultimately, our success.

We were looking for an easy and seamless integration that we could get up and running quickly to collect core web vital metrics for our products. We have been using Amazon CloudWatch RUM to monitor our website performance, specifically page load times, JavaScript errors, and other core web vital metrics. Using RUM has helped our team collect and measure real-world performance metrics of our websites, while also giving us a unified way to collect and analyze that data. What made RUM stand out was how it integrated seamlessly with our products and other parts of CloudWatch, allowing us to use collected data for further processing, without the added worry of loss of connectivity or data shortage.

AWS innovation with CloudWatch RUM has enabled Cognizant to advance our operations automation framework to the next level by providing the granular visibility and control our clients require, without needing third-party solutions. On-boarding CloudWatch RUM was easy, seamless, and integrated with the native services we are currently utilizing. We discovered features that enabled outstanding visibility including categorizing application response from different browsers with load times, page load Gantt chart with custom dates, application load results by time, and ability to generate reports using pdf.

We have invested heavily on observability and monitoring on our application’s microservice architecture but were missing the outside-in monitoring to ensure the product was stable and reliable for our customers. Using Amazon CloudWatch Synthetics, we are now able to simulate real users to monitor uptime availability, filling a gap in our observability stack. We are creating canaries to reflect our user journeys through our product and are alerted to live issues before our customers. CloudWatch Synthetics allows us to capture our Service Level Agreements (SLAs) and reduce our Mean Time to Resolution (MTTR) by enabling us to triage and debug. CloudWatch Synthetics is really simple to setup. The Synthetics Recorder allows team members beyond our engineers to generate canaries to greatly increase the relevance and value of the service within EBSCO.

We were looking to consolidate all our monitoring, logging, metrics, and alerting under one tool. CloudWatch has helped us alleviate the operational burden to set up, configure, and learn third-party systems. Our teams use CloudWatch extensively to monitor error rates and status codes for multiple high-profile workloads. We also use CloudWatch to automate Auto Scaling actions, allowing us to optimize the cost of Amazon EC2 instance types powering our Amazon ECS clusters. CloudWatch Events enable us to provide utilization and pricing information to teams so they can audit account security, trigger AWS Lambda actions for compliance and security use cases, and schedule our resources using the cloud. CloudWatch enables next-level automation and expands the capacity of each individual.

Our current log analytics solution requires setup and maintenance overhead, has differing retention requirements, and is cost prohibitive, making it impossible for our Engineering team to be able to access and query logs in both development and test environments. With CloudWatch Logs Insights, we are now able to query logs within CloudWatch Logs reducing operational complexity. Pay per query gives us flexibility to scale at our own pace and our engineers can begin to consume and query logs without waiting for the setup, integration, and ingestion to take place with our current solution. We also benefit from viewing metrics and logs allowing faster troubleshooting. Logs Insights is an effective and inexpensive solution for our engineers to monitor their applications and perform log diving all from single AWS console.

CloudWatch allows us to collect metrics from AWS services such as Amazon EC2, Amazon Kinesis, Amazon DynamoDB, and Amazon API Gateway, as well as logs from AWS Lambda functions. We appreciated being able to integrate natively, without the need for a self-managed stack or third-party SaaS vendor. This helped us start alerting, auto scaling, and capacity planning very quickly. Being able to address our primary use cases quickly and simply made CloudWatch a preferred solution.

Amazon CloudWatch enables CloudPassage to perform indexed searches of tens of gigabytes of logs daily. Using CloudWatch Logs, the company manages and analyzes logs in one place, whether they are received from Amazon ECS, AWS Fargate, AWS CodeBuild, or custom sources. “We use a microservices-based architecture. Amazon CloudWatch was an instant solution as it required no infrastructure set up or maintenance. CloudWatch has no issues handling our scale and removed the operational burden of integrating and managing multiple tools. The most important benefit for us is the decrease in MTTR (mean time to repair), as our DevOps team can quickly find issues across our container infrastructure. Our customers benefit from this by experiencing a stable platform, which enables faster discovery and fixes of potential bugs as well as accelerated feature development. Less time finding and fixing bugs in existing functionality means more time for our developers to spend building new features.

Amazon CloudWatch has enabled us to seamlessly integrate Canva’s microservice backend architecture with our logging framework. We chose CloudWatch because it has simplified the process to aggregate various types of logs streams from various AWS services, and reduced the overhead costs and complexity generally associated with logs management. CloudWatch also supports the ability to export certain logs via log streams which enabled us to set up an external automated log analysis pipeline, so it was a clear winner.

We adopted AWS services to gain control of our infrastructure. Amazon CloudWatch tackles this issue head-on by providing detailed visibility into any issues in real time. By analyzing patterns and monitoring data closely, CloudWatch allows us to detect and avoid potential issues during crunch business time. With automated event-driven actions, like alerting and scaling, we have reduced detection time from days to mere minutes. And using Amazon CloudWatch Logs Insights, we can identify the true pain points in the system and proactively solve for potential issues that become difficult to manage at scale. CloudWatch has ultimately allowed us to dynamically manage infrastructure resources, allowing us to increase our cost savings by 70% each month (web infrastructure alone).

We use CloudWatch to monitor and trigger automated audit checks of deployed resources. Each team has to manage its own AWS environment, and with CloudWatch, we can build specific guardrails around these accounts. Because we can also monitor for changes to tags and track the tag state on AWS resources, we have been able to increase our tag compliance by 50% helping with AWS cost reporting. With centralized governance and distributed operations, we have been able to dramatically lower costs and meet all requirements for IT compliance and audit readiness.

We implemented CloudWatch because we needed a centralized service to store logs and pull metrics from the logs. For example, using Amazon CloudWatch Logs, we can alert on the number of log lines that match ‘error.’ In addition, Amazon CloudWatch Logs Insights has dramatically simplified the process of searching large volumes of logs. We can now derive actionable insights from this data, allowing us to address operational issues and improve application performance across our organization. With this solution, our developers can devote more time to the Arctic Wolf SOC-as-a-service.

Amazon CloudWatch was a natural choice for us for monitoring our infrastructure on AWS and on premises. Our Application teams and developers now have a way to collect and access all performance and operational data via logs and metrics across all our accounts and regions from a single platform. This benefit has impacted their everyday lives, as they can now drive resiliency in the applications that we build to support our customers.

We use CloudWatch to create alerts for Amazon Simple Queue Service and for scaling actions for EC2 Auto Scaling Groups. These insights inform our scaling decisions, allowing us to get the most efficient usage out of our AWS compute resources without impacting our customers’ experience. With CloudFormation, we can deploy logical stacks for our AWS resources used by our customer-facing applications, which provides us with repeatable and consistent deployments across AWS accounts. As a result, we have an easy way to compose application stacks using configuration-as-code, rather than relying on error-prone manual configuration that can be inconsistent.