Akamai has introduced Managed Service for API Performance, a managed offering that combines continuous synthetic testing, 24/7 monitoring, and expert-led optimization to ensure that APIs — the true circulatory system of the digital economy — remain fast, resilient, and compliant with increasingly demanding regulatory frameworks. The solution leverages the APIContext platform and is designed with cross-cutting applicability: from multicloud to hybrid environments, with an explicit focus on end-to-end visibility (DNS, SSL/TLS, Internet delivery, and third-party dependencies).
This move comes at a crucial time. APIs have become the default layer of integration for digital products and services: payments, identity, logistics, reservations, customer service, analytics… Everything travels through endpoints that must authenticate, authorize, orchestrate flows, and comply with diverse regulations such as DORA (EU financial services), NIS2 (critical infrastructures), MAS TRM (Singapore), or SEC SCI (U.S.). In this context, Akamai’s promise is to reduce operational friction: less time firefighting and more capacity to prevent issues, with forensic evidence ready for audits.
From Monitoring to Management: what’s included in the new offering
The service goes beyond adding just another performance dashboard to the “observability zoo.” Its approach combines managed services with purpose-built technical tools:
- 24/7 synthetic testing and expert intervention. The platform performs continuous synthetic calls from multiple locations and networks, validates authentication, schemes, and flows, and triggers alerts upon degradations or outages. The key difference here is the “expert-in-the-loop”: a team of analysts verifies incidents and prioritizes responses to avoid alert noise and fatigue.
- CUSTOMIZED action plans and executive reporting. Beyond metrics, the service delivers improvement plans that optimize everything from alert sensitivity to flow design (e.g., retries, timeouts, exponential backoff, dependency ordering). Reports translate technical data into business impact, highlighting trends, bottlenecks, and risks.
- Expert guidance and detection of hidden patterns. Through time-series analysis and traces, specialists identify intermittent slowdowns, schema mismatches, recurrent endpoint errors, or geographical anomalies (e.g., degradations limited to specific AS or regions).
- Validation against OpenAPI and regulatory frameworks. The service compares APIs to their OpenAPI specifications, detects drifts and contract violations, and provides compliance-oriented views demonstrating, with data, availability, latency, and adherence to requirements (DORA, NIS2, MAS TRM, SEC SCI, and other industry standards).
- Infrastructure and delivery chain visibility. It monitors multicloud environments, DNS, SSL/TLS configurations, and the internet delivery path, helping distinguish whether bottlenecks are in code, network, identity provider, a CDN, or an upstream dependency.
- Baseline performance metrics and “audit-ready” evidence. Establishes measurable baselines to evaluate improvements and degradations, and records each synthetic call with full traceability. The result is an inviolable record suitable for audits or regulatory requirements.
The strategic message is clear: seeing the problem isn’t enough; you must take on its resolution, like an extended SRE team for critical APIs. That’s the gap Akamai aims to fill.
Why now: APIs as a competitive advantage (or as a vulnerability)
For years, many organizations treated APIs as a byproduct of development. Today, they are products in their own right: with SLA, lifecycle, catalog, pricing (sometimes), and, most importantly, internal and external consumers depending on their performance. Any failure point can lead to sales funnels, blocked operations, and reputational damage.
The issue is that traditional monitoring—focused on hosts, containers, and processes—fails to capture the semantic of the API: versioning, contracts, rate-limit policies, authentication mechanisms (OAuth 2.0, OIDC, rotating keys, MTLS), idempotency, staged payments, or multi-step flows. Synthetic tests are needed to exercise real use cases, validate schemas and responses, and measure user experience as perceived by a client or microservice.
Adding to this is the complexity of the distributed environment: microservices, queues, databases, caches, external providers, and increasingly, AI models embedded in workflows (translation, enrichment, classification). Knowing that a pod is “Ready” doesn’t guarantee the API serves; knowing an endpoint returns 200 OK doesn’t ensure it complies with contract or responds on time under load.
Security and performance: two sides of the same coin
While the announcement positions the offering around performance, its architecture directly influences the security surface of an API. Validating schemas reduces the entropy that injection or deserialization attacks exploit; monitoring authentication detects expiry, claim misalignments, and lax configurations; tracing routes helps reveal exposed services unintentionally. In a world where APIs and API security go hand-in-hand, adopting a resilience approach—performance + compliance + visibility—proves more practical than siloed measures.
Further, the emphasis on regulations is not superficial. In finance, healthcare, or critical infrastructure, regulators are beginning to demand operational resilience tests, evidence of availability and response times, and test procedures and audits. Here, a complete record of synthetic calls and receipt acknowledgments of alerts/actions are invaluable.
What does this mean for technical teams?
For SREs, platform teams, and observability specialists, the service introduces three practical improvements:
- Realistic functional coverage. Synthetic tests are designed per flow: reproducing call sequences, tokens, and dependencies as a real consumer would. This detects orchestration failures, not just immediate outages.
- Actionable prioritization. An expert team filters false positives, associates incidents with recent changes (deployments, certificate rotations, new routes), and proposes concrete adjustment points (e.g., misaligned timeouts, aggressive caches).
- Evidence and governance. With clear baselines and forensic traces, interactions with business and risk teams are rooted in data. This allows prioritizing technical debt and planning capacity with confidence, not guesswork.
For architects and product owners, the benefit lies in translating technical KPIs (p50, p95, p99, error rate, saturation) into experience indicators per flow: checkout, onboarding, payment, identity verification, order tracking, etc.
Multicloud and real internet: the importance of path
A key differentiator of this service is its focus on the end-to-end delivery chain. Many issues are not in the microservice itself but in DNS resolution, expired certificates, overly strict WAF rules, misconfigured CORS policies, or congested network hops between providers. Tests from multiple regions and networks reveal degradations that internal tests from the VPC would never detect.
In multicloud scenarios, knowing whether anycast functions as intended, whether BGP routing introduces latency for certain ISPs, or if a regional identity provider adds seconds to authentication flows can be the difference between meeting or missing SLAs.
Performance and compliance: from “best effort” to “audit-ready”
Another important vector is compliance. Mentioning DORA, NIS2, MAS TRM, and SEC SCI highlights that this service is designed with regulated organizations in mind. These standards push for demonstrable operational resilience: it’s not enough to say “the API was available”; you must prove it with records, traces, and reproducible methodologies.
The “audit-ready” approach —with every synthetic call recorded with integrity and traceability— aligns technology with governance. It enables more robust responses to regulator requests or post-incident investigations.
How does this fit with existing observability stacks?
Akamai itself proposes integration with already-deployed observability tools (metrics, logs, traces), so that the service acts as a specialized source rather than another silo. The correlation of synthentic tests, APM, infrastructure metrics, and security logs offers a comprehensive view that few teams can assemble alone, especially when performance and security boundaries blur.
A partner to “offload” work: more predictability, fewer firefights
Organizationally, the value lies in outsourcing a repetitive, thankless task — fine-tuning APIs. Maintaining robust synthetic tests, updating contracts, monitoring supplier changes, and documenting evidence often compete with the product roadmap. A managed service reduces this load and provides budget predictability.
This doesn’t replace a skilled internal team; it complements it. The interaction between Akamai’s team and the client’s platform/SRE teams determines success: which flows are tested, how SLIs/SLOs are defined, thresholds trigger responses, and what automations are deployed (e.g., rollbacks or automatic scaling).
Risks and limitations: what the service doesn’t solve on its own
It’s important to avoid overhyping. A managed service will not eliminate:
- Fragile designs: if the architecture is prone to failure cascades, observability will detect symptoms, not cure the root cause.
- Chronic technical debt: without time and budget to refactor or decouple, improvements remain incremental.
- Responsibility gaps: even the best report doesn’t substitute for product decisions, prioritization, and change management.
That said, having trustworthy data, useful alerts, and specific recommendations raises the internal conversation bar and makes it easier to gain traction for significant investments.
Looking ahead: APIs, AI, and new demands
As more AI workloads are integrated into business flows, latency and consistency SLAs become tougher: an inference endpoint introducing uncontrolled variability can break entire experiences. Synthetic instrumentation simulating real-world cases — including robust authentication routes, transformations, enrichment, and third-party calls— will become increasingly strategic.
Moreover, with growing regulatory fragmentation, organizations will need tests and evidence adapted to jurisdiction and vertical. Explicit references to frameworks like DORA or NIS2 suggest Akamai will align the service to new requirements as they emerge, providing reassurance to CIOs and CISOs.
Frequently Asked Questions
How does a managed API performance service differ from traditional monitoring tools?
While a tool provides metrics and dashboards, the managed service incorporates people and processes: designing and maintaining flow-based synthetic tests, incident validation to reduce noise, delivering action plans, and producing audit-ready evidence for compliance. The result is lower MTTR and better governance.
How does this help meet regulations like DORA or NIS2?
Through continuous tests that verify availability and latency against defined baselines, validation against OpenAPI, and maintaining integrity records of each call with traceability. This offers objective evidence for auditors and regulators, and supports operational resilience plans.
Is this applicable if my architecture is multicloud or hybrid?
Yes. The service observes the entire delivery chain: DNS, SSL/TLS, internet routing, external providers, and various clouds. Tests from multiple regions and networks reveal regional anomalies and bottlenecks that internal monitors alone wouldn’t detect.
What impact does this have on SRE and platform teams?
It frees capacity by outsourcing parts of test maintenance, event correlation, and evidence documentation. It provides prioritized recommendations and executive reporting to align business and risk with the technical reality. It does not replace the internal team; it amplifies it.
Sources consulted:
Akamai Technologies — Press release about Managed Service for API Performance.
APIContext — Corporate information on monitoring and compliance capabilities for APIs.