Data Feed SLA (Service Level Agreement)

The Uptime Guarantee is a core SLA metric, expressed as a percentage (e.g., 99.9%), that defines the minimum acceptable time the data feed is operational and accessible. This is typically measured over a monthly or quarterly period. Breaching this threshold triggers service credits or other contractual remedies.

• Example: A 99.9% uptime SLA allows for approximately 43 minutes of downtime per month.
• Measurement: Often calculated as (Total Time - Downtime) / Total Time, where downtime includes all periods where the feed fails to deliver data within the defined latency window.

Update Latency (or data freshness) specifies the maximum allowable delay between a real-world event (e.g., an on-chain transaction) and its reflection in the data feed. This is critical for time-sensitive applications like derivatives pricing or liquidations.

• Primary Metric: Usually defined as a p99 or p95 value (e.g., "p99 latency < 500ms"), meaning 99% of updates are delivered within that time.
• Components: Includes source latency (block propagation), computation time (oracle node processing), and network transmission.

This feature guarantees the accuracy of the provided data against a defined truth source. It often includes mechanisms to detect and respond to incorrect data.

• Deviation Thresholds: Triggers an alert or pauses the feed if the reported price deviates from a consensus of other sources by more than a set percentage (e.g., 2%).
• Validity Proofs: Some SLAs may require cryptographic attestations that the data was correctly computed from the agreed-upon sources.
• Remedy: A data incorrectness event typically results in the most severe penalties, as it can directly cause user financial loss.

The SLA defines the cryptoeconomic security model protecting the data feed, quantifying the cost to attack or manipulate it. This is not just a technical feature but a financial guarantee.

• Key Metrics: Total value of staked collateral or bonded assets that can be slashed for misbehavior.
• Node Operator Set: Specifications on the number and independence of oracle nodes (e.g., minimum of 31 independent node operators).
• Transparency: Commitments to open-source software, verifiable on-chain data posting, and publicly auditable node performance.

The remedy framework that is enacted when the provider fails to meet the SLA specifications. It translates service failures into financial consequences, aligning incentives.

• Service Credits: The typical remedy involves refunding a portion of the service fees paid by the user for the period of the failure.
• Escalating Penalties: Penalties often scale with the severity and duration of the breach. A prolonged downtime or a data incorrectness event incurs a larger credit than a minor latency spike.
• Claims Process: The SLA must define a clear, objective process for users to submit and verify claims for credits.

Commitments regarding the observability of the service's performance against its SLA metrics. Users cannot claim credits if they cannot measure breaches.

• Public Dashboards: Real-time status pages showing current uptime, latency percentiles, and data correctness.
• Historical Reports: Regularly published (e.g., monthly) attestation reports that log all performance data and any SLA breaches.
• On-Chain Verification: For blockchain-native feeds, key heartbeat and data attestation transactions provide an immutable, verifiable audit trail.

The most fundamental SLA metric, expressed as a percentage (e.g., 99.9%). It measures the proportion of time the data feed is operational and accessible over a defined period (monthly/quarterly). Downtime includes total outages and periods where the feed delivers stale or invalid data beyond the agreed tolerance.

• Calculation: (Total Time - Downtime) / Total Time
• Example: 99.9% uptime allows for ~43 minutes of downtime per month.
• Importance: Directly impacts application reliability and user trust.

Guarantees the maximum delay between an on-chain event (like a trade) and its reflection in the data feed. This is critical for DeFi protocols needing real-time prices for liquidations or swaps.

• Measured in: Milliseconds or seconds (e.g., < 1 second p95 latency).
• Key Components: Includes block propagation time, oracle node processing, and data delivery.
• SLA Structure: Often defined as a percentile (p95, p99) to account for network variability.

The guarantee that the provided data correctly reflects the state of the blockchain. This includes correct pricing, token balances, and transaction status. SLAs define thresholds for price deviation from a consensus of sources and mechanisms for invalid data detection.

• Deviation Checks: SLA may specify a feed will not deviate more than X% from a benchmark (e.g., a volume-weighted median).
• Validity Window: Defines the time to detect and correct erroneous data broadcasts.
• Root Cause: Failures often stem from oracle manipulation attacks or source exchange outages.

Defines the volume of data requests the service guarantees to handle, typically measured in requests per second (RPS) or queries per second (QPS). This ensures the feed can scale with application demand without degradation.

• Guaranteed Throughput: The minimum sustained RPS the provider commits to (e.g., 1,000 RPS).
• Burst Capacity: A higher, short-term limit allowed for peak loads.
• Consequences: Exceeding limits may result in throttling or failed requests, violating the SLA.

The contractual remedies provided to the customer when the provider fails to meet SLA guarantees. This is typically financial compensation, not a service fix.

• Service Credit: A percentage refund of the monthly fee for each SLA breach (e.g., 10% credit for uptime below 99.9%).
• Credit Caps: Maximum total credit per period (e.g., capped at 100% of monthly fee).
• Critical Distinction: Credits are the sole remedy; they do not cover downstream losses from application failures.

The provider's obligation to transparently measure, report, and verify SLA compliance. This includes providing customers with access to:

• Real-time Status Pages: Showing current system health.
• Historical Reports: Detailed logs of uptime, latency, and any incidents.
• Root Cause Analysis (RCA): For significant breaches.
• Independent Verification: Some providers use third-party attestations or on-chain verification (e.g., proof of data publication) to prove compliance.

A cryptoeconomic security model where data providers post collateral (stake) that is forfeited if they violate SLA terms. This creates direct financial disincentives for downtime or incorrect data. Key implementations include:

• Bond-based slashing: A fixed bond is slashed for a proven violation.
• Continuous slashing: Penalties accrue proportionally to the duration or severity of the failure, such as missed updates.

Performance is tracked to create a reputation score or adjust a node's effective stake weight. Nodes with a strong history of meeting SLAs are rewarded with:

• Higher selection probability for data requests.
• A greater share of rewards (like fees or incentives).
• Conversely, poor performance reduces influence and earnings, creating a non-financial enforcement layer.

Automated, periodic checks that verify a data feed is active and responsive. These are technical enforcement mechanisms that trigger alerts or penalties. Common methods include:

• On-chain heartbeat transactions: Oracles must submit regular transactions to prove liveness.
• Challenge-response protocols: The network or users can challenge a data point, forcing the provider to cryptographically prove its validity within a time window.

Reliability is enforced by sourcing data from multiple, independent providers. The system aggregates responses (e.g., median) to produce a single tamper-resistant value. This model includes:

• Consensus-based validation: Data is considered valid only when a quorum of nodes agrees.
• Dispute resolution periods: Users can dispute published data, initiating a verification and slashing process if fraud is proven.

A traditional cloud SLA model adapted for Web3, where the provider compensates users with service credits for downtime or latency breaches. This is often codified in smart contracts for automated payout. For example, a contract might refund a proportional amount of the usage fee if uptime falls below 99.5% in a billing cycle.

Protocols like Aave, Compound, and Uniswap rely on oracle SLAs for price feed integrity. Their smart contracts specify:

• Minimum Oracle Count: Requiring data from multiple independent sources.
• Heartbeat & Deviation: Conditions that force a price update to prevent stale or manipulated data.
• Liquidation Safety: SLAs ensure liquidations are triggered based on accurate, timely prices, protecting protocol solvency. A failure in the SLA can lead to under-collateralized loans or incorrect swap rates.

Optimistic and ZK Rollups (e.g., Arbitrum, zkSync) use SLAs in their sequencer or prover services. These SLAs guarantee:

• State Finality Time: Maximum delay for transaction inclusion and state commitment to Layer 1.
• Data Availability: Ensuring transaction data is posted to Ethereum within a specified timeframe for security.
• Uptime: Commitment to sequencer availability, often backed by economic penalties or a decentralized fallback mechanism.

Bridges (e.g., Axelar, LayerZero) implement SLAs for message delivery and state verification. Critical SLA metrics include:

• Delivery Latency: Maximum time for a cross-chain message to be delivered and executable.
• Validity Proof Submission: Guarantee that validity proofs or attestations are submitted on the destination chain within a deadline.
• Guardian/Relayer Performance: SLAs for the network of entities responsible for relaying messages, with slashing for liveness failures.

Platforms like The Graph (for indexing) or Arweave (for permanent storage) provide SLAs for data services.

• The Graph Indexers: SLA for query latency and indexing uptime, with rewards and slashing based on performance.
• Arweave Storage Providers: SLA for data permanence and retrievability, enforced by cryptographic proof-of-access and financial staking. These SLAs form the basis for reliable decentralized application backends.

The mechanisms that make SLAs credible and actionable:

• On-Chain Verification: SLA compliance is often verified by smart contracts that automatically check timestamps, data freshness, and proofs.
• Staking & Slashing: Node operators or service providers post stake (bond) that can be slashed for SLA violations.
• Reputation Systems: Performance against SLAs is tracked in on-chain reputation scores, influencing future delegation and rewards.
• Fallback Oracles & Circuits: Protocols implement backup data sources that activate if the primary SLA is breached.

Uptime is the percentage of time a data feed is operational and delivering correct data within the expected latency window. It is the core metric in an SLA, often expressed as "five nines" (99.999%). Availability is closely related but may refer to the broader accessibility of the oracle network's infrastructure. SLAs define the minimum acceptable uptime, with penalties (slashing) or service credits applied if the target is not met.

Data freshness refers to how recent the provided data is, while latency is the time delay between a real-world event and its on-chain availability. An SLA specifies maximum acceptable latency (e.g., "< 2 seconds"). For financial data like price feeds, low latency is critical to prevent arbitrage and front-running. This is often measured as heartbeat (how often updates are posted) and deviation thresholds (how much the price must move to trigger an update).

A Data Feed's security is intrinsically linked to the decentralization of its oracle network. Key security models include:

• Node Operator Diversity: Independent, geographically distributed, and sybil-resistant nodes.
• Cryptoeconomic Security: Staked collateral (bond) that can be slashed for providing incorrect data or downtime.
• Transparent Monitoring: On-chain verification of node performance and SLA compliance.

Staking is the process where node operators lock collateral (often the oracle's native token) to participate in the network and provide data. Slashing is the punitive mechanism that automatically deducts a portion of this staked collateral if the operator violates the SLA (e.g., downtime, incorrect data). This creates a strong economic incentive for reliable performance and is a foundational element of a credible, trust-minimized SLA.

Data aggregation is the process of combining data from multiple independent sources (e.g., CEXs, DEXs) and oracle nodes to produce a single, tamper-resistant value. Methods include:

• Medianization: Taking the median value to filter out outliers.
• Time-weighted Average Price (TWAP): Calculating an average over a period to smooth volatility. The aggregation method is a critical design choice that impacts the feed's resistance to manipulation and is a key component of its SLA specification.