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OpenTelemetry Integration

Turn Observability into Foresight with Perviewsis

OpenTelemetry is the future of open observability—collecting standardized traces, metrics, and logs from across your stack. Perviewsis takes that raw telemetry and elevates it with predictive insights, causal modeling, and workflow automation, helping you go far beyond dashboards.

With Perviewsis OpenTelemetry, you can see what’s happening now, know what’s next, and act automatically.

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Key Features

Seamless Integration

Perviewsis integrates directly with the Dynatrace API to ingest high-resolution metrics, topology maps, and Davis AI problem reports in real time.

  • Syncs service metrics, SLOs, logs, and events
  • Ingests Davis problem data and AI insights
  • Correlates application, infrastructure, and cloud platform metrics
  • Supports tag-based resource grouping and custom filters

The result is a unified data layer across observability and automation platforms—with zero disruption to your Dynatrace setup.

Predictive Analytics Engine

ynatrace detects current issues. Perviewsis predicts what’s next.

Using time-series forecasting and pattern recognition, Perviewsis continuously analyzes historical Dynatrace data to:

  • Predict slowdowns, outages, or saturation risks before they happen
  • Flag silent regressions in services, SLOs, or cloud resources
  • Estimate time-to-impact for developing anomalies
  • Automatically adjust baselines for seasonality and workload shifts

Example: Forecast CPU exhaustion in a Kubernetes pod 3 hours before the Davis AI triggers a problem alert.

Causal Relationship Mapping

With Perviewsis, you’re not just watching metrics—you’re understanding their causes.

By analyzing the relationships between Dynatrace telemetry and other observability sources, Perviewsis identifies causal links and root issues faster than traditional correlation methods.

  • Build causal graphs across services, containers, and dependencies
  • Reduce noise by tracing alerts to single upstream issues
  • Prioritize response based on downstream business or user impact

Example: A drop in conversion rate traced back to frontend latency caused by a memory leak in a backend service hosted on an over-provisioned node.

Intelligent Automation & Orchestration

Perviewsis lets you build smart responses to insights from Dynatrace—automatically.

  • Define event-driven workflows triggered by Dynatrace anomalies, metrics, or SLO violations
  • Automate actions like scaling, restart, ticketing, or notification
  • Integrate with third-party tools (Slack, Jira, PagerDuty, GitOps pipelines, Terraform, etc.)
  • Include prediction confidence and root cause metadata in automation triggers

All through a visual, low-code automation builder.

Unified Observability and Action Hub

Perviewsis merges Dynatrace telemetry with other data sources to provide a true 360° view of your environment:

  • Application metrics
  • Infrastructure health
  • Business KPIs
  • User behavior

Deployment metadata

This cross-domain visibility helps teams collaborate across silos and accelerate incident resolution.

Key Use Cases

Proactive Cloud Performance Optimization

Anticipate cloud resource saturation and scale intelligently to avoid costly performance drops.

Deployment Risk Detection

Identify anomalies or regressions linked to new deployments using Dynatrace and CI/CD metadata together.

SLO Forecasting

Predict upcoming SLO breaches before users are impacted. Generate early warnings with time-to-violation metrics.

Root Cause Feedback to Dev Teams

Surface causality trees to dev teams directly via integrations, giving context to every alert or issue.

How It Works

  • Connect your Dynatrace environment using Perviewsis guided integration
  • Select metrics, entities, and events to import
  • Set up predictions, causal links, and workflow rules
  • Monitor and act—all from one intelligent observability interface

Native OTel Compatibility

Perviewsis supports native ingestion of OpenTelemetry data via:

  • OTLP (OpenTelemetry Protocol): gRPC and HTTP support
  • Push & Pull modes: Compatible with OTLP exporters, collectors, and agents
  • Flexible schema mapping for custom instrumentation
  • Support for spans, traces, metrics, and logs

Whether you’re instrumenting microservices, infrastructure, or frontend apps, Perviewsis connects seamlessly to your existing OTel pipeline—no vendor lock-in, no agent sprawl.

Predictive Telemetry Engine

Raw telemetry is reactive. 

By analyzing time-series metrics and trace patterns, Perviewsis forecasts upcoming issues and slowdowns across your stack:

  • Predict latency regressions in distributed traces
  • Forecast CPU, memory, or I/O saturation at the service or pod level
  • Detect trends indicating SLO breaches before they occur
  • Automatically adjust anomaly baselines based on workload changes

Example: Forecast a 120ms increase in end-to-end transaction time based on trends across three upstream services instrumented via OTel.

Causal Correlation & Root Cause Analysis

Perviewsis builds causal maps from OpenTelemetry spans and traces to identify true root causes—especially in complex microservice architectures.

  • Analyze service-to-service dependencies across distributed systems
  • Identify which span or component caused a performance anomaly
  • Correlate telemetry with external sources (e.g., logs, deployment metadata
  • Map performance issues to downstream business impact (e.g., checkout drop-off)

Example: An error spike traced back to a single Kafka topic stall, affecting four downstream services and end-user conversion.

Low-Code Automation on Telemetry Events

Perviewsis allows teams to create event-driven workflows based on OpenTelemetry signals and predicted anomalies:

  • Trigger actions on custom span attributes, log errors, or predicted failures
  • Automatically notify teams, open incidents, or execute remediation scripts
  • Integrate with CI/CD, ITSM, and ChatOps tools (Jira, GitHub, PagerDuty, Slack)
  • Use confidence scores and causal metadata to prioritize automation

All within a drag-and-drop workflow builder designed for Ops, Devs, and SREs alike.

Full-Stack Observability, Enhanced

OpenTelemetry provides unified observability. Perviewsis transforms it into:

  • Predictive alerting without rigid thresholds
  • Causal tracing across services, infrastructure, and users
  • Automated root cause diagnosis
  • SLO-aware observability with forecasted violations
  • Business-contextual dashboards tying metrics to outcomes

Perviewsis helps you understand why things happen and what to do about it—before your users notice.

Use Cases :

Proactive Incident Detection

Forecast outages and slowdowns in microservices before traces degrade or users report issues.

SLO Breach Forecasting

Use telemetry data to predict when a service is trending toward SLO violation—and act preemptively.

Root Cause Discovery in Distributed Systems

Trace errors or slowness to the exact span, dependency, or deployment change that triggered them.

Intelligent Workflow Orchestration

Build automated responses triggered by trace patterns, logs, or predictions (e.g., rollback deployments, scale services).

How It Works

Ingest OTel Data

Connect your OTLP exporters or OpenTelemetry Collector to Perviewsis (HTTP/gRPC support).

Map Telemetry to Services

Perviewsis auto-discovers your service topology and spans using metadata and trace context.

Enable Predictions & RCA

Train models on your metrics and traces, enabling forecasting and causal graphs.

Automate Smartly

Use telemetry signals or prediction triggers to launch workflows and alerts.

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