Search Results for "file-studio"

...Zero Code distributed tracing powered by eBPF supports applications in any language and infrastructures including gateways, service meshes, databases, message queues, DNS, and NICs, leaving no blind spots. Full-stack network performance metrics and file I/O events are automatically collected for each Span. Distributed tracing enters a new era, Zero Instrumentation. DeepFlow collects profiling data at a cost of below 1% with Zero Code, plots OnCPU/OffCPU function call stack flame graphs, and locates Full Stack performance bottleneck in the application.

Tetragon is a flexible Kubernetes-aware security observability and runtime enforcement tool that applies policy and filtering directly with eBPF, allowing for reduced observation overhead, tracking of any process, and real-time enforcement of policies. Observe the complete lifecycle of every process on your machine with Kubernetes context awareness. Translate high-level policies for file monitoring, network observability, container security, and more into low-overhead eBPF programs. Synchronous monitoring, filtering, and enforcement completely in the kernel with eBPF.

...Loggie includes LogConfig/ClusterLogConfig/Interceptor/Sink CRDs, allowing for the creation of data collection, transfer, processing, and sending pipelines through simple YAML file creation. Supports deployment as an independent intermediate machine, which can receive aggregated data sent by Loggie Agent and can also be used to consume and process various data sources. Configure Filebeat and Loggie to collect logs, and send them to a Kafka topic without using client compression, with the Kafka topic partition configured as 3. ...

...Traffic streams may be compressed and/or encrypted using TLS. The PacketStreamer receiver accepts PacketStreamer streams from multiple remote sensors and writes the packets to a local pcap capture file. PacketStreamer sensors collect raw network packets on remote hosts. It selects packets to capture using a BPF filter, and forwards them to a central receiver process where they are written in pcap format. Sensors are very lightweight and impose little performance impact on the remote hosts. PacketStreamer sensors can be run on bare-metal servers, on Docker hosts, and on Kubernetes nodes.

This tool allows exporting the often missed Kubernetes events to various outputs so that they can be used for observability or alerting purposes. You won't believe what you are missing. Configuration is done via a YAML file, when run in Kubernetes, ConfigMap. The tool watches all the events and the user has to option to filter out some events, according to their properties. Critical events can be routed to alerting tools such as Opsgenie, or all events can be dumped to an Elasticsearch instance. You can use namespaces, and labels on the related object to route some Pod-related events to owners via Slack. ...