Best Telemetry Software in the Middle East - Page 2

Identify and resolve performance issues and errors within your microservices architecture. Establish connections between root causes by analyzing traces, logs, and metrics. Reduce your costs associated with OpenTelemetry traces through Aspecto's integrated remote sampling feature. The way OTel data is visualized plays a crucial role in enhancing your troubleshooting efficiency. Transition seamlessly from a broad overview to intricate details using top-tier visualization tools. Link logs directly to their corresponding traces effortlessly, maintaining context to expedite issue resolution. Utilize filters, free-text searches, and grouping options to navigate your trace data swiftly and accurately locate the source of the problem. Optimize expenses by sampling only essential data, allowing for trace sampling based on programming languages, libraries, specific routes, and error occurrences. Implement data privacy measures to obscure sensitive information within traces, specific routes, or other critical areas. Moreover, integrate your everyday tools with your operational workflow, including logs, error monitoring, and external event APIs, to create a cohesive and efficient system for managing and troubleshooting issues. This holistic approach not only improves visibility but also empowers teams to tackle problems proactively.

Eliminate delays, pinpoint inefficiencies, and troubleshoot problems effectively. Become a part of a swiftly growing network of global businesses that are realizing up to 20 times the value and return on investment by utilizing KloudMate, far exceeding other observability platforms. Effortlessly track essential metrics, relationships, and identify irregularities through alerts and tracking issues. Swiftly find critical 'break-points' in your application development process to address problems proactively. Examine service maps for each component within your application while revealing complex connections and dependencies. Monitor every request and operation to gain comprehensive insights into execution pathways and performance indicators. Regardless of whether you are operating in a multi-cloud, hybrid, or private environment, take advantage of consolidated Infrastructure monitoring features to assess metrics and extract valuable insights. Enhance your debugging accuracy and speed with a holistic view of your system, ensuring that you can detect and remedy issues more quickly. This approach allows your team to maintain high performance and reliability in your applications.

Phoenix serves as a comprehensive open-source observability toolkit tailored for experimentation, evaluation, and troubleshooting purposes. It empowers AI engineers and data scientists to swiftly visualize their datasets, assess performance metrics, identify problems, and export relevant data for enhancements. Developed by Arize AI, the creators of a leading AI observability platform, alongside a dedicated group of core contributors, Phoenix is compatible with OpenTelemetry and OpenInference instrumentation standards. The primary package is known as arize-phoenix, and several auxiliary packages cater to specialized applications. Furthermore, our semantic layer enhances LLM telemetry within OpenTelemetry, facilitating the automatic instrumentation of widely-used packages. This versatile library supports tracing for AI applications, allowing for both manual instrumentation and seamless integrations with tools like LlamaIndex, Langchain, and OpenAI. By employing LLM tracing, Phoenix meticulously logs the routes taken by requests as they navigate through various stages or components of an LLM application, thus providing a clearer understanding of system performance and potential bottlenecks. Ultimately, Phoenix aims to streamline the development process, enabling users to maximize the efficiency and reliability of their AI solutions.

Pydantic Logfire serves as an observability solution aimed at enhancing the monitoring of Python applications by converting logs into practical insights. It offers valuable performance metrics, tracing capabilities, and a comprehensive view of application dynamics, which encompasses request headers, bodies, and detailed execution traces. Built upon OpenTelemetry, Pydantic Logfire seamlessly integrates with widely-used libraries, ensuring user-friendliness while maintaining the adaptability of OpenTelemetry’s functionalities. Developers can enrich their applications with structured data and easily queryable Python objects, allowing them to obtain real-time insights through a variety of visualizations, dashboards, and alert systems. In addition, Logfire facilitates manual tracing, context logging, and exception handling, presenting a contemporary logging framework. This tool is specifically designed for developers in search of a streamlined and efficient observability solution, boasting ready-to-use integrations and user-centric features. Its flexibility and comprehensive capabilities make it a valuable asset for anyone looking to improve their application's monitoring strategy.

ServiceNow Cloud Observability provides real-time visibility and monitoring of cloud infrastructure, applications and services. It allows organizations to identify and resolve performance problems by integrating data from different cloud environments into a single dashboard. ServiceNow Cloud Observability's advanced analytics and alerting features help IT and DevOps departments detect anomalies, troubleshoot issues, and ensure optimal performance. The platform supports AI-driven insights and automation, allowing teams the ability to respond quickly to incidents. Overall, the platform improves operational efficiency while ensuring a seamless user-experience across cloud environments.

Transmit your data points using the established protocol for IoT and telemetry data. We retain all your information with precision, capturing details down to the millisecond, which enhances your high-resolution applications. Our system guarantees at least once processing while incorporating data deduplication throughout the process. Data is streamed and processed in real-time, ensuring that you receive your results immediately upon availability. Furthermore, our data exploration module empowers you to perform queries on your data, enabling you to analyze and dissect it thoroughly to uncover the insights you need. With these tools, you can make more informed decisions based on comprehensive data analysis.

Network Telemetry: VPC Flow Logs Detecting traffic and access trends that could pose security or operational threats to your organization is achievable in near real-time. Network Telemetry equips both network and security teams with comprehensive and responsive VPC flow logs specifically designed for Google Cloud networking services. Firewall Logging: With VPC Firewall Logs, users can efficiently record both access and denied events of the firewall, enjoying the same level of responsiveness provided by VPC flow logs. Monitoring at Peak Performance: VPC flow logs enable you to oversee your deployments without affecting system performance. Thanks to our innovative approach, activating VPC flow logs grants you extensive visibility without introducing any performance drawbacks. Additionally, the integration of these tools enhances your overall network security posture.

IoT Edge Connect offers a protocol for real-time communication and data processing specifically designed for devices connected to Akamai. Utilizing both the message queuing telemetry transport (MQTT) and HTTP protocols, it efficiently ingests messages while ensuring that data is processed and sent back to devices instantly through a publish-subscribe model. This MQTT-centric system enables seamless reading from and writing to message queues, automatically delivering messages organized by topics. Additionally, the HTTP interface allows for an alternative method of accessing the same message queues that the MQTT protocol utilizes, enabling clients to request messages in topic form via a REST API. Overall, IoT Edge Connect enhances connectivity and data flow between devices and the cloud, providing flexibility in how messages are handled and delivered.

Enhance your security operations with Falcon XDR, which elevates detection and response capabilities throughout your security infrastructure. At its core is leading endpoint protection, and Falcon XDR integrates telemetry from various domains to offer security personnel a centralized, threat-focused command interface. Elevate your EDR capabilities by utilizing consolidated telemetry from multiple platforms, which significantly improves threat correlation and accelerates response efforts against advanced threats. Speed up threat analysis and proactive hunting by converting isolated, fragmented data into robust, cross-platform indicators of attack, actionable insights, and timely alerts. Transform insights gained from XDR into coordinated actions, enabling security teams to create and automate comprehensive, multi-stage response workflows for precise, full-spectrum remediation. This not only streamlines operations but also enhances the effectiveness of your security measures.

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.

Uptrace is an observability platform built on OpenTelemetry that enables users to track, comprehend, and enhance intricate distributed systems effectively. With a single, streamlined dashboard, you can oversee your entire application stack efficiently. This setup provides a swift view of all services, hosts, and systems in one place. The distributed tracing feature allows you to follow the journey of a request as it flows through various services and components, highlighting the timing of each operation along with any logs and errors that arise in real-time. Through metrics, you can swiftly gauge, visualize, and monitor a variety of operations using tools such as percentiles, heatmaps, and histograms. By receiving alerts when your application experiences downtime or when a performance issue is detected, you can respond to incidents more promptly. Moreover, the platform allows you to monitor all aspects—spans, logs, errors, and metrics—using a unified query language, simplifying the observability process further. This comprehensive approach ensures that you have all the necessary insights to maintain optimal performance in your distributed systems.

Small Hours serves as an AI-driven observability platform designed to diagnose server exceptions, evaluate their impact, and direct them to the appropriate personnel or team. You can utilize Markdown or your current runbook to assist our tool in troubleshooting various issues effectively. We offer seamless integration with any stack through OpenTelemetry support. You can connect to your existing alerts to pinpoint critical problems swiftly. By linking your codebases and runbooks, you can provide necessary context and instructions for smoother operations. Rest assured, your code and data remain secure and are never stored. The platform intelligently categorizes issues and can even generate pull requests as needed. It is specifically optimized for enterprise-scale performance and speed. With our 24/7 automated root cause analysis, you can significantly reduce downtime while maximizing operational efficiency, ensuring your systems run smoothly at all times.

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.

Aggregate all your data seamlessly using Enterprise plugins such as Splunk, ServiceNow, Datadog, and others. The integrated collaboration tools enable teams to engage efficiently from a unified dashboard. With enhanced security and compliance features, you can rest assured that your data remains protected at all times. Gain insights from experts in Prometheus, Graphite, and Grafana, along with dedicated support teams ready to assist. While other providers may promote a "one-size-fits-all" database solution, Grafana Labs adopts a different philosophy: we focus on empowering your observability rather than controlling it. Grafana Enterprise offers access to a range of enterprise plugins that seamlessly integrate your current data sources into Grafana. This innovative approach allows you to maximize the potential of your sophisticated and costly monitoring systems by presenting all your data in a more intuitive and impactful manner. Ultimately, our goal is to enhance your data visualization experience, making it simpler and more effective for your organization.

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.

Fluent Bit is capable of reading data from both local files and network devices, while also extracting metrics in the Prometheus format from your server environment. It automatically tags all events to facilitate filtering, routing, parsing, modification, and output rules effectively. With its built-in reliability features, you can rest assured that in the event of a network or server failure, you can seamlessly resume operations without any risk of losing data. Rather than simply acting as a direct substitute, Fluent Bit significantly enhances your observability framework by optimizing your current logging infrastructure and streamlining the processing of metrics and traces. Additionally, it adheres to a vendor-neutral philosophy, allowing for smooth integration with various ecosystems, including Prometheus and OpenTelemetry. Highly regarded by prominent cloud service providers, financial institutions, and businesses requiring a robust telemetry agent, Fluent Bit adeptly handles a variety of data formats and sources while ensuring excellent performance and reliability. This positions it as a versatile solution that can adapt to the evolving needs of modern data-driven environments.

A specialized application performance monitoring tool tailored for distributed systems, particularly optimized for microservices, cloud-native environments, and containerized architectures like Kubernetes. One SkyWalking cluster has the capacity to collect and analyze over 100 billion pieces of telemetry data. It boasts capabilities for log formatting, metric extraction, and the implementation of diverse sampling policies via a high-performance script pipeline. Additionally, it allows for the configuration of alarm rules that can be service-centric, deployment-centric, or API-centric. The tool also has the functionality to forward alarms and all telemetry data to third-party services. Furthermore, it is compatible with various metrics, traces, and logs from established ecosystems, including Zipkin, OpenTelemetry, Prometheus, Zabbix, and Fluentd, ensuring seamless integration and comprehensive monitoring across different platforms. This adaptability makes it an essential tool for organizations looking to optimize their distributed systems effectively.

It aids in collecting timing information essential for diagnosing latency issues within service architectures. Its functionalities encompass both the gathering and retrieval of this data. When you have a trace ID from a log, you can easily navigate directly to it. If you don't have a trace ID, queries can be made using various parameters such as service names, operation titles, tags, and duration. Additionally, notable data is summarized, including the proportion of time spent on each service and the success or failure of operations. The Zipkin user interface also features a dependency diagram that illustrates the volume of traced requests processed by each application. This visualization can be instrumental in recognizing overall patterns, including error trajectories and interactions with outdated services. Overall, this tool not only simplifies the troubleshooting process but also enhances the understanding of service interactions within complex architectures.

Enhanced high-definition APM visibility through real user monitoring, synthetic monitoring, and OpenTelemetry offers a solution that is scalable, user-friendly, and simplifies the integration of insights from end users, applications, networks, and the cloud-native space. The rise of microservices within containerized environments on dynamic cloud infrastructures has resulted in a highly transient and distributed landscape at an unprecedented scale. Traditional methods of enhancing APM, which rely on sampled transactions, partial traces, and aggregate metrics, have become ineffective, as legacy APM solutions struggle to identify the reasons behind slow or stalling critical business applications. The Riverbed platform provides cohesive visibility across the contemporary application landscape, ensuring ease of deployment and management, while facilitating quicker resolution of even the most challenging performance issues. Riverbed APM is thoroughly designed for the cloud-native environment, offering extensive monitoring and observability for transactions that operate on the latest cloud and application infrastructures, ultimately enhancing operational efficiency and user experience. This comprehensive approach not only addresses current performance challenges but also positions organizations to adapt to future technological advancements seamlessly.

Improving business outcomes involves making it easier to spot and address high-priority incidents. The WatchTower Platform serves as a comprehensive observability tool that streamlines incident resolution specifically within mainframe environments by effectively integrating and correlating events, data flows, and metrics across various IT silos. It provides a cohesive and intuitive interface for operations teams, allowing them to optimize their workflows. Leveraging established AIOps solutions, WatchTower is adept at detecting potential problems at an early stage, which aids in proactive mitigation. Additionally, it utilizes OpenTelemetry to transmit mainframe data and insights to observability tools, allowing enterprise SREs to pinpoint bottlenecks and improve operational effectiveness. By enhancing alerts with relevant context, WatchTower eliminates the necessity for logging into multiple tools to gather essential information. Its workflows expedite the processes of problem identification, investigation, and incident resolution, while also simplifying the handover and escalation of issues. With such capabilities, WatchTower not only enhances incident management but also empowers teams to proactively maintain high service availability.

DataBahn is an advanced platform that harnesses the power of AI to manage data pipelines and enhance security, streamlining the processes of data collection, integration, and optimization from a variety of sources to various destinations. Boasting a robust array of over 400 connectors, it simplifies the onboarding process and boosts the efficiency of data flow significantly. The platform automates data collection and ingestion, allowing for smooth integration, even when dealing with disparate security tools. Moreover, it optimizes costs related to SIEM and data storage through intelligent, rule-based filtering, which directs less critical data to more affordable storage options. It also ensures real-time visibility and insights by utilizing telemetry health alerts and implementing failover handling, which guarantees the integrity and completeness of data collection. Comprehensive data governance is further supported by AI-driven tagging, automated quarantining of sensitive information, and mechanisms in place to prevent vendor lock-in. In addition, DataBahn's adaptability allows organizations to stay agile and responsive to evolving data management needs.

Tenzir is a specialized data pipeline engine tailored for security teams, streamlining the processes of collecting, transforming, enriching, and routing security data throughout its entire lifecycle. It allows users to efficiently aggregate information from multiple sources, convert unstructured data into structured formats, and adjust it as necessary. By optimizing data volume and lowering costs, Tenzir also supports alignment with standardized schemas such as OCSF, ASIM, and ECS. Additionally, it guarantees compliance through features like data anonymization and enhances data by incorporating context from threats, assets, and vulnerabilities. With capabilities for real-time detection, it stores data in an efficient Parquet format within object storage systems. Users are empowered to quickly search for and retrieve essential data, as well as to reactivate dormant data into operational status. The design of Tenzir emphasizes flexibility, enabling deployment as code and seamless integration into pre-existing workflows, ultimately seeking to cut SIEM expenses while providing comprehensive control over data management. This approach not only enhances the effectiveness of security operations but also fosters a more streamlined workflow for teams dealing with complex security data.

PacketRanger is a cutting-edge SaaS platform hosted on the web that simplifies the creation and management of telemetry pipelines throughout the entire IT environment by analyzing, filtering, duplicating, and directing data from various sources to countless destination consumers. It allows for the swift development of pipelines that reduce irrelevant data, set volumetric baselines with adjustable alert thresholds, and delivers comprehensive visual tools to identify both low- and high-value data alongside network problems and configuration errors. Tailored specifically for NetFlow, it helps alleviate congestion, enhances flow-based licensing, minimizes duplicate UDP packets, accommodates all versions of NetFlow/IPFIX, provides more than 400 predefined and custom filter templates, reduces packet loss, and addresses exporter constraints. In its functionality for Syslog, it guarantees even event distribution, straightforward keyword and regex filtering, support for TCP/TLS, automatic message parsing without the need for manual grok patterns, and the capability to convert logs into SNMP traps, thereby vastly improving operational efficiency and data management. Ultimately, PacketRanger stands out as an essential tool for any organization looking to streamline their telemetry processes and gain deeper insights into their network performance.

Sawmills stands out as the pioneering smart telemetry management platform that empowers businesses to manage their logs, metrics, and traces efficiently before incurring expenses from traditional observability tools. Its innovative use of AI for noise detection sets it apart from other solutions in the market, allowing Sawmills to effectively minimize waste, enhance data integrity, and enforce governance measures. Unlike conventional filtering methods and manually crafted rules, which often fall short in scalability, Sawmills leverages AI to analyze telemetry data in real-time, identifying noise patterns, duplicate events, low-value attributes, excessive cardinality, PII/policy breaches, and faulty schemas. For every issue detected, Sawmills suggests a corresponding action—options include filtering, redacting, aggregating, downsampling, normalizing, enriching, and it features the ability to auto-remediate with necessary approvals, service level agreements, and rollbacks. This proactive approach not only shifts oversight upstream but also significantly decreases waste, enhances the quality of the data being collected, and automates governance, ultimately leading to more efficient data management practices across enterprises.