Health Check

A liveness probe determines if a containerized application or node process is running. If it fails, the orchestrator (e.g., Kubernetes) restarts the container. This addresses issues where the process is stuck in a deadlock but the OS process is still active.

• Purpose: Detect and recover from a crashed or unresponsive process.
• Example: An HTTP GET request to a /healthz endpoint that must return a 200 status code within a timeout period.

A readiness probe determines if an application is ready to accept traffic. A failing probe signals the orchestrator to remove the pod from service load balancers until it passes.

• Purpose: Prevent traffic from being sent to a pod that is still booting, loading large datasets, or is temporarily overloaded.
• Example: A TCP socket check that succeeds only after the application's database connections are fully established.

A startup probe is used for legacy applications with long initialization times. It disables liveness and readiness checks until the startup probe succeeds, preventing the orchestrator from killing the application before it has a chance to start.

• Purpose: Handle slow-starting containers without triggering restart loops.
• Mechanism: Once successful, the probe is disabled, and liveness/readiness probes take over for the remainder of the container's lifecycle.

In blockchain node operation, a health check verifies the execution client (e.g., Geth, Erigon) is synchronized and functioning. This is critical for validators and RPC providers.

• Common Checks: Peer count, sync status (eth_syncing), latest block timestamp, and CPU/memory usage.
• Failure Impact: A failing execution client will cause a validator to miss attestations and proposals, leading to inactivity leaks and slashing risk.

For Proof-of-Stake networks like Ethereum, a separate health check monitors the consensus client (e.g., Lighthouse, Prysm). It ensures the node can participate in blockchain consensus.

• Key Metrics: Attestation performance, validator status (active, slashed), head slot advancement, and participation in sync committees.
• Integration: Often paired with execution client checks for a complete node health assessment.

Health checks are implemented using one of three primary mechanisms:

• HTTP GET: The most common. A request is sent to a specified path; a response code between 200-399 indicates success.
• TCP Socket: The probe attempts to open a TCP connection to a specified port. Success is based on establishing a connection.
• Command Execution: The probe executes a command inside the container. A zero exit code indicates success.

This assesses the economic incentives securing the network. Key indicators are:

• Total Value Locked (TVL) in staking or DeFi.
• Validator participation rate and slashing events.
• Inflation/reward rates and token supply dynamics.
• Staking ratio (percentage of circulating supply staked). A high, stable staking ratio with minimal slashing indicates a healthy, secure Proof-of-Stake network.

Evaluating the user experience and network congestion through transaction metrics. This includes monitoring average transaction fees, confirmation times, mempool size, and failed transaction rates. Sudden spikes in fees or confirmation times can indicate network stress, while consistently low usage may signal low adoption. Services like GasNow (historically for Ethereum) and blockchain scanners provide this data.

Measuring the network's resilience to attacks and censorship. Critical checks include:

• Hash rate distribution (PoW) or validator set distribution (PoS).
• Client diversity to avoid single-client dominance.
• Governance participation rates.
• Status of bug bounty programs and recent security audits. High decentralization across clients and validators is a primary indicator of robust health.

In a multi-chain world, the health of cross-chain bridges is paramount. Checks involve verifying the total value bridged, the security model of the bridge (e.g., validators, multi-sig, light clients), and monitoring for any frozen funds or exploit announcements. A bridge failure represents a critical systemic risk to the interconnected ecosystem.

The primary function of a health check is to provide a binary status indicator (e.g., 'healthy' or 'unhealthy') for a system component. It performs automated probes to verify:

• Liveliness: Is the service running and accepting connections?
• Readiness: Is the service prepared to handle requests (e.g., synced with the network)?
• Functionality: Do critical RPC endpoints and smart contract queries return expected results? This allows for automated remediation, such as restarting failed processes or rerouting traffic.

A comprehensive health check evaluates multiple layers of the stack:

• Infrastructure: CPU, memory, and disk usage of the node server.
• Network: Peer connections, latency to other nodes, and RPC endpoint responsiveness.
• Blockchain State: Current block height, synchronization status, and fork detection.
• Smart Contract Dependencies: Verification that dependent external contracts or oracles are accessible and returning valid data.
• Economic Security: For validators, checks on staked balance and slashing conditions.

Health checks are the foundational data source for operational monitoring. They integrate with systems like Prometheus, Grafana, or PagerDuty to:

• Trigger alerts when a service degrades or fails.
• Provide dashboards for real-time visibility into system state across a node fleet.
• Enable automated scaling in cloud environments, spinning up new instances if health checks fail. This creates a feedback loop essential for maintaining high availability in decentralized systems.

Beyond uptime, health checks are a critical security control. They can detect:

• Sybil Attacks: By monitoring peer count and identifying suspicious connection patterns.
• Chain Reorganizations: Alerting on unexpected fork depths that could indicate a 51% attack.
• Oracle Failure: Detecting when price feeds or data oracles become stale or manipulatable.
• Configuration Drift: Ensuring security-critical settings (e.g., RPC authentication) have not been inadvertently changed.

Developers implement health checks using several standard patterns:

• HTTP Endpoint: A /health endpoint that returns a 200 OK status and a JSON payload with component statuses.
• Readiness & Liveness Probes: Used in container orchestration (e.g., Kubernetes) to manage pod lifecycle.
• Heartbeat Mechanisms: Periodic signed messages from a service to a monitoring dashboard to prove liveness.
• Consensus Health: For validators, checks that involve signing a test message to verify the private key is accessible and functional.

Health checks interact closely with other operational concepts:

• Circuit Breaker: A design pattern that uses health check failures to stop sending requests to a failing service.
• Service Discovery: Dynamic registries that use health checks to add or remove instances from a load balancer pool.
• SLIs & SLOs (Service Level Indicators/Objectives): Health check success rates are a fundamental SLI for measuring reliability.
• Watchdog Timer: A hardware or software timer that resets a system if a health check signal is not received periodically.