Best Observability Tools in Brazil - Page 4

Enhance both your production and staging environments by integrating logs, metrics, and traces in real-time and on-demand directly from your IDE or command line interface. With Lightrun, you can significantly improve productivity and achieve complete code-level visibility. You can add logs and metrics instantly while services are operational, making it easier to debug complex architectures like monoliths, microservices, Kubernetes, Docker Swarm, ECS, and serverless applications. Quickly insert any missing log lines, instrument necessary metrics, or establish snapshots as needed without the hassle of recreating the production setup or redeploying. When you invoke instrumentation, the resulting data gets sent to your log analysis platform, IDE, or preferred APM tool. This allows for thorough analysis of code behavior to identify bottlenecks and errors without interrupting the running application. You can seamlessly incorporate extensive logs, snapshots, counters, timers, function durations, and much more without risking system stability. This streamlined approach lets you focus on coding rather than getting bogged down in debugging, eliminating the need for constant restarts or redeployments when troubleshooting. Ultimately, this results in a more efficient development workflow, allowing you to maintain momentum on your projects.

LOGIQ.AI's LogFlow offers a unified management system for your observability data pipelines. As data streams are received, they are efficiently categorized and optimized to serve the needs of your business teams and knowledge workers. XOps teams can streamline their data flow management, enhancing data EPS control while also improving the quality and relevance of the data. LogFlow’s InstaStore, built on any object storage solution, provides limitless data retention and allows for on-demand data playback to any observability platform you prefer. This enables the analysis of operational metrics across various applications and infrastructure, yielding actionable insights that empower you to scale confidently while ensuring consistent high availability. By collecting, transforming, and analyzing behavioral data and usage trends from business systems, you can enhance business decisions and improve user experiences. Furthermore, in an ever-evolving threat landscape, it's essential to stay ahead; with LogFlow, you can identify and analyze threat patterns coming from diverse sources, automating both threat prevention and remediation processes effectively. This proactive approach not only strengthens security but also fosters a resilient operational environment.

Bigeye is a platform designed for data observability that empowers teams to effectively assess, enhance, and convey the quality of data at any scale. When data quality problems lead to outages, it can erode business confidence in the data. Bigeye aids in restoring that trust, beginning with comprehensive monitoring. It identifies missing or faulty reporting data before it reaches executives in their dashboards, preventing potential misinformed decisions. Additionally, it alerts users about issues with training data prior to model retraining, helping to mitigate the anxiety that stems from the uncertainty of data accuracy. The statuses of pipeline jobs often fail to provide a complete picture, highlighting the necessity of actively monitoring the data itself to ensure its suitability for use. By keeping track of dataset-level freshness, organizations can confirm pipelines are functioning correctly, even in the event of ETL orchestrator failures. Furthermore, the platform allows you to stay informed about modifications in event names, region codes, product types, and other categorical data, while also detecting any significant fluctuations in row counts, nulls, and blank values to make sure that the data is being populated as expected. Overall, Bigeye turns data quality management into a proactive process, ensuring reliability and trustworthiness in data handling.

Our ready-to-use solution empowers you to keep an eye on your cluster's health and resolve problems more swiftly with intuitive dashboards that function seamlessly. Coupled with transparent and budget-friendly pricing, initiating your journey is a breeze. ContainIQ operates three agents within your cluster: one single replica deployment that gathers metrics and events from the Kubernetes API, along with two daemon sets—one dedicated to capturing latency data for every pod on the node and the other focused on logging for all pods and containers. You can monitor latency metrics by microservice and path, including p95, p99, average response times, and requests per second (RPS). The system works immediately without the need for additional application packages or middleware. Set alerts to notify you of significant changes and utilize search functionality to filter by date ranges while observing data trends over time. You can see all incoming and outgoing requests along with their associated metadata. Additionally, visualize P99, P95, average latency, and error rates over time for each specific URL path, and correlate logs for a particular trace, which is invaluable for troubleshooting when issues occur. This comprehensive approach ensures you have all the tools needed to maintain optimal performance and swiftly diagnose any challenges that arise.

Navigating performance visibility in today’s intricate IT landscapes can be quite challenging, particularly with applications that traverse traditional data centers, SaaS, and IaaS cloud setups. A conventional, siloed management approach often leads to a disjointed and incomplete understanding of performance metrics. Consequently, IT teams find themselves dedicating significant time to data analysis, frequently arriving at divergent and sometimes contradictory insights regarding the root causes of performance issues. The Riverbed Portal addresses this issue by consolidating performance telemetry, resulting in a unified and dynamic overview of performance metrics. This comprehensive perspective provides IT operations teams with a reliable single source of truth, which streamlines troubleshooting processes and delivers valuable insights for stakeholders across the organization. Ultimately, this enables IT to effectively manage and enhance applications, data, and traffic within the entire hybrid network, allowing key resources to concentrate on high-priority strategic initiatives while reducing the likelihood of performance-related disputes. By fostering a clearer understanding of performance, teams can make informed decisions that drive overall efficiency and effectiveness within the organization.

When organizations choose to invest in a comprehensive observability platform that integrates data, insights, and actions throughout their IT landscape, they are able to address issues more swiftly while also removing data silos, reducing the need for resource-intensive war rooms, and alleviating alert fatigue. The Riverbed IQ unified observability solution empowers both business and IT to make quick and effective decisions by encapsulating expert troubleshooting knowledge, enabling less experienced staff to deliver more first-level resolutions, which in turn fosters digital innovation and enhances the overall digital experience for both customers and employees. By utilizing broad-based telemetry, organizations can attain a cohesive view of performance and insights, establishing a solid foundation of unified observability that supports the delivery of all other capabilities. Riverbed IQ’s methodology towards unified observability initiates with our full-fidelity telemetry, which spans across network and infrastructure components and incorporates metrics related to the end-user experience, ensuring a comprehensive understanding of system performance. This holistic approach not only streamlines troubleshooting but also positions organizations to respond adeptly to evolving digital demands.

Chaos Genius serves as a DataOps Observability platform specifically designed for Snowflake, allowing users to enhance their Snowflake Observability, thereby minimizing costs and improving query efficiency. By leveraging this platform, organizations can gain deeper insights into their data operations and make more informed decisions.

Kensu provides real-time monitoring of the complete data usage quality, empowering your team to proactively avert data-related issues. Grasping the significance of data application is more crucial than merely focusing on the data itself. With a unified and comprehensive perspective, you can evaluate data quality and lineage effectively. Obtain immediate insights regarding data utilization across various systems, projects, and applications. Instead of getting lost in the growing number of repositories, concentrate on overseeing the data flow. Facilitate the sharing of lineages, schemas, and quality details with catalogs, glossaries, and incident management frameworks. Instantly identify the underlying causes of intricate data problems to stop any potential "datastrophes" from spreading. Set up alerts for specific data events along with their context to stay informed. Gain clarity on how data has been gathered, replicated, and altered by different applications. Identify anomalies by analyzing historical data patterns. Utilize lineage and past data insights to trace back to the original cause, ensuring a comprehensive understanding of your data landscape. This proactive approach not only preserves data integrity but also enhances overall operational efficiency.

AI-powered cloud observation platform. Middleware platform helps you identify, understand and resolve issues across your cloud infrastructure. AI will detect and diagnose all issues infra, application and infrastructure and provide better recommendations for fixing them. Dashboard allows you to monitor metrics, logs and traces in real time. The best and fastest results with the least amount of resources. Bring all metrics, logs and traces together into a single timeline. A full-stack platform for observability will give you complete visibility into your cloud. Our AI-based algorithms analyze your data and make suggestions for what you should fix. Your data is yours. Control your data collection, and store it in your cloud to save up to 10x the cost. Connect the dots to determine where the problem began and where it ended. Fix problems before users report them. The users get a comprehensive solution for cloud observability at a single location. It's also too cost-effective.

Grafana Phlare allows you to consolidate continuous profiling data while ensuring high availability, multi-tenancy, and reliable storage solutions, which enhances your insight into application resource usage at a granular level. As an open-source database, Grafana Phlare offers rapid, scalable, and efficient storage alongside querying capabilities for profiling data. The inception of Phlare took place during a company-wide hackathon at Grafana Labs, and the project was officially introduced in 2022 at ObservabilityCON. Its primary objective is to facilitate large-scale continuous profiling for the open-source community, empowering developers with a deeper comprehension of their code's resource consumption. This initiative ultimately aids users in evaluating their application performance and fine-tuning their infrastructure expenditures, leading to more efficient application management.

Enhancing service and support efficiency, alongside business satisfaction, begins with the ability to foresee and prevent downtime. EV Observe serves as a comprehensive monitoring platform tailored for networks, IoT devices, IT infrastructure, cloud environments, and application monitoring, ensuring a seamless end-to-end service experience. Our solution empowers organizations to adopt a proactive and predictive stance towards service support, delivery, and observability, facilitating collaborative self-help and self-healing capabilities, as well as providing in-depth insights into performance and availability. This approach enables teams to concentrate on delivering value and fostering innovation that propels business success, ultimately leading to greater employee engagement, enriched customer experiences, heightened productivity, and enhanced resiliency. Specifically designed for SaaS monitoring in a multi-client and multi-site environment, it also integrates a comprehensive software production tool that encompasses the entire range of software processes while promoting the implementation of DevOps practices for optimized operational efficiency. The holistic nature of our platform ensures that organizations can adapt swiftly to changing demands in the digital landscape.

Enhance the security of your OpenAI interactions by implementing enterprise-grade features tailored for robust oversight. While OpenAI's LLM APIs offer remarkable capabilities, they often fall short in providing the detailed control and transparency that larger organizations require. Usage Panda addresses these shortcomings effectively. It scrutinizes security protocols for each request prior to submission to OpenAI, ensuring compliance. Prevent unexpected charges by restricting requests to those that stay within predetermined cost limits. Additionally, you can choose to log every request, along with its parameters and responses, for thorough tracking. The platform allows for the creation of an unlimited number of connections, each tailored with specific policies and restrictions. It also empowers you to monitor, censor, and block any malicious activities that seek to manipulate or expose system prompts. With Usage Panda's advanced visualization tools and customizable charts, you can analyze usage metrics in fine detail. Furthermore, notifications can be sent to your email or Slack when approaching usage caps or billing thresholds, ensuring you remain informed. You can trace costs and policy breaches back to individual application users, enabling the establishment of user-specific rate limits to manage resource allocation effectively. This comprehensive approach not only secures your operations but also enhances your overall management of OpenAI API usage.

Pinghome stands out as the foremost provider of top-tier cloud-based uptime monitoring solutions. Our straightforward mission is to equip you with essential tools and insights that guarantee your websites and APIs operate seamlessly at all times. We prioritize delivering outstanding service, beginning with our talented team of skilled and enthusiastic developers. Their commitment and expertise allow us to address all your website monitoring requirements, ensuring you receive unmatched assistance and direction throughout the entire process. Furthermore, we continually strive to innovate and enhance our offerings to better serve our clients in an ever-evolving digital landscape.

LMOps is a stack that allows you to launch production-ready applications for monitoring, model management and more. Portkey is a replacement for OpenAI or any other provider APIs. Portkey allows you to manage engines, parameters and versions. Switch, upgrade, and test models with confidence. View aggregate metrics for your app and users to optimize usage and API costs Protect your user data from malicious attacks and accidental exposure. Receive proactive alerts if things go wrong. Test your models in real-world conditions and deploy the best performers. We have been building apps on top of LLM's APIs for over 2 1/2 years. While building a PoC only took a weekend, bringing it to production and managing it was a hassle! We built Portkey to help you successfully deploy large language models APIs into your applications. We're happy to help you, regardless of whether or not you try Portkey!

Revolutionizing observability brings context and performance into a unified space, suitable for any stack and scale. Achieve thorough end-to-end visibility by effortlessly monitoring applications, infrastructure, databases, and more from a single, user-friendly dashboard. With just a few clicks, trace and analyze digital journeys seamlessly from browsers and applications to the infrastructure layer. Discover invaluable insights into user experiences, identify where dropouts occur, and highlight critical aspects of business transactions through in-depth user analytics and real user monitoring (RUM). This allows for quick adaptation, optimization, and innovation powered by real-time visibility and swift root-cause analysis. Additionally, our dedicated team of experts is available 24/7, 365 days a year, ensuring you receive prompt assistance and tailored support for your unique requirements, which further enhances your operational efficiency. The combination of these features empowers businesses to stay ahead in a rapidly evolving digital landscape.

HTCD is an AI-driven cloud security SaaS designed to significantly enhance your security posture. HTCD offers centralized visibility with over 500 pre-built policies covering cloud security, infrastructure, networks, SaaS, and compliance. You retain full control of your data while benefiting from seamless integration and extensive protection. Detect - No-Code Detection Engineering Eliminate the need for complex coding. With HTCD, create detections without code, using plain English as your programming language. Quickly identify and mitigate potential threats with queries like: "Which CVEs are exploitable in my Azure environment?" "Show me S3 costs over the past two weeks." Hunt - Proactive Internal Threat Hunting Track activities across all your Cloud (Azure, AWS) and SaaS (M365, GitHub, HubSpot, Slack, etc.) tools with ease. Empower your security analysts and internal threat detection teams with one-click hunting for rapid detection and resolution. Respond - Address What Matters Most Gain a risk-based perspective on security misconfigurations and vulnerabilities, prioritized by AI specifically for you. HTCD helps you address the most critical issues, drastically reducing response times and operational risk.

Introducing your discreet partner for a vendor-neutral unified data collection solution: Cribl Edge is a smart and highly scalable system designed for edge-based data collection, encompassing logs, metrics, and application information. With features such as automatic log discovery and metrics generation, Cribl Edge caters to the needs of modern distributed microservice architectures. You can easily deploy, configure, and manage your agents from a central location, allowing for seamless scalability and reduced resource overhead while maintaining the flexibility to avoid vendor lock-in through agnostic integrations. Transitioning away from numerous outdated agents, you can eliminate overlapping proprietary systems to simplify your operations, minimize attack surfaces, and lower expenses. Bid farewell to tedious manual upgrades by empowering your team with a centralized platform for agent management. Moreover, effectively handle your widespread infrastructure, enabling the swift deployment and monitoring of thousands of nodes within days rather than weeks, ultimately streamlining your entire data management process.

SolarWinds Observability Self-Hosted, previously referred to as Hybrid Cloud Observability, serves as a robust, all-encompassing observability platform tailored to assist businesses in maintaining system uptime and shortening remedial efforts across both on-premises and multi-cloud infrastructures by enhancing visibility, intelligence, and overall efficiency. This solution consolidates data from various components of the IT landscape, including networks, servers, applications, databases, and more, to deliver a cohesive perspective on service performance and component interrelations. Key functionalities of the platform include monitoring network performance, analyzing traffic flows, managing network device configurations, overseeing IP address allocations, tracking users and devices, as well as managing servers and applications. Additionally, it supports virtualization oversight, log monitoring and analysis, server configuration governance, and quality assurance for VoIP and network services. By providing these integrated features, SolarWinds helps organizations proactively address issues and optimize their IT environments.

Middleware Observability & management software for Messaging, event processing, and Streaming Across Hybrid Clouds (MESH). - 360 degree situational awareness® with complete observability of Integration MESH - Manage configuration, administration and deployment in a secure manner and automate them. - Track and trace transactions, messages, and flows - Collect data, monitor performance, and benchmark it meshIQ provides granular controls for managing configurations in the MESH, reducing downtime and allowing quick recovery after outages. It allows you to search, browse, track and trace messages in order to detect bottlenecks, speed up root cause analysis, and detect bottlenecks. Unlocks integration blackbox for visibility across MESH infrastructure in order to visualize, analyse, report and predict. Delivers the capability to trigger automated action based on predefined criteria or intelligent AI/ML actions.

Kentik provides the network analytics and insight you need to manage all your networks. Both old and new. Both the ones you have and those you don't. All your traffic from your network to your cloud to the internet can be viewed on one screen. We offer: - Network Performance Analytics - Hybrid Analytics and Multi-Cloud Analytics (GCP. AWS. Azure) Internet and Edge Performance Monitoring - Infrastructure Visibility DNS Security and DDoS Attack Defense - Data Center Analytics - Application Performance Monitoring Capacity Planning Container Networking - Service Provider Intelligence - Real Time Network Forensics - Network Costs Analytics All on One Platform for Security, Performance, Visibility Trusted by Pandora and Box, Tata, Yelp. University of Washington, GTT, and many other! Try it free!

Security and observability tailored for Kubernetes environments. Implementing security and observability as code is essential for modern cloud-native applications. This approach encompasses cloud-native security as code for various elements, including hosts, virtual machines, containers, Kubernetes components, workloads, and services, ensuring protection for both north-south and east-west traffic while facilitating enterprise security measures and maintaining continuous compliance. Furthermore, Kubernetes-native observability as code allows for the gathering of real-time telemetry, enhanced with context from Kubernetes, offering a dynamic view of interactions among components from hosts to services. This enables swift troubleshooting through machine learning-driven detection of anomalies and performance issues. Utilizing a single framework, organizations can effectively secure, monitor, and address challenges in multi-cluster, multi-cloud, and hybrid-cloud environments operating on either Linux or Windows containers. With the ability to update and deploy security policies in mere seconds, businesses can promptly enforce compliance and address any emerging issues. This streamlined process is vital for maintaining the integrity and performance of cloud-native infrastructures.

Enhance the connectivity, security, monitoring, and management of your distributed enterprise edge through a centralized system of observability and analytics. By identifying and addressing problems more swiftly, you can achieve improved uptime, performance, and security. The open microservices architecture provides all the necessary tools to effectively oversee your distributed enterprise edge, ensuring seamless operation and maintenance. This integrated approach not only streamlines processes but also boosts overall efficiency across your organization.

Tanzu Observability by Broadcom is an advanced observability solution designed to provide businesses with deep visibility into their cloud-native applications and infrastructure. The platform aggregates metrics, traces, and logs to deliver real-time insights into application performance and operational health. By leveraging AI and machine learning, Tanzu Observability automatically detects anomalies, accelerates root cause analysis, and offers predictive analytics to optimize system performance. With its scalable architecture, the platform supports large deployments, enabling businesses to manage and improve the performance of their digital ecosystems efficiently.

Rookout is a live data collection platform and debugging platform that allows software engineers to understand any application, no matter where it is running. This includes monolithic applications to cloud native ones. Rookout enables engineers to reduce debugging time and log time by 80%. This allows them to solve customer problems 5x faster. Software engineers can access the data they need instantly with Non-Breaking Breakpoints. This is without any additional coding, restarts or redeployment. Developers can extract the data they need from any line of code. This makes it easier to collaborate and facilitate handoffs.

You can innovate faster in the cloud, improve user experience and future-proof applications. Splunk is designed for cloud-native enterprises and helps you solve current problems. Splunk helps you detect any problem before it becomes a customer problem. Our AI-driven Directed Problemshooting reduces MTTR. Flexible, open-source instrumentation eliminates lock-in. Optimize performance by seeing all of your application and using AI-driven analytics. You must observe everything in order to deliver an excellent end-user experience. NoSample™, full-fidelity trace ingestion allows you to leverage all your trace data and identify any anomalies. Directed Troubleshooting reduces MTTR to quickly identify service dependencies, correlations with the underlying infrastructure, and root-cause errors mapping. You can break down and examine any transaction by any dimension or metric. You can quickly and easily see how your application behaves in different regions, hosts or versions.