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Solutions · Observability for Developers

Debug your own service.
Without paging the SRE.

Applicare gives every developer a plain-English interface to the logs, traces, metrics, and infrastructure events from their own service. Find the bug. Get the explanation. Ship the fix — without the relay race to SRE, without learning SPL, without a war room.

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Trusted by engineering teams at · AeroMexico · Leading Private Bank · NTT DATA · Danube Group · ONP · ATN · Abril · Seygen · AeroMexico · Leading Private Bank · NTT DATA ·
Why observability matters across the SDLC

Observability is the engineering practice of understanding production from the outside — what your service did, why it did it, and what to do next. Done well, it shortens the loop between “something’s wrong” and “I’ve fixed it.” Done poorly, it produces three separate dashboards and a Slack thread that ends with “works on my machine.” Applicare treats logs, traces, metrics, infrastructure, and database signals as one causal graph — queryable in plain English, owned by the developer who owns the code.

80%
Reduction in SRE escalations
<60s
Developer self-service root cause
0
PromQL or SPL fluency required
Why these numbers matter

The developer who wrote the code is the fastest person to fix the bug — if they can see the signal. Applicare removes the three friction points that stop them today: waiting for SRE help, learning a query language, and stitching three tools together.

80%

Fewer escalations to SRE. Developers diagnose their own services without escalating. SRE focuses on platform reliability, not playing detective on someone else’s code.

<60s

From symptom to root cause. Ask ArcIn a question, get an answer with the responsible service, span, log line, and commit attached — in under a minute. No 30-minute investigation rituals.

0

Accessible to every engineer. No PromQL, no SPL, no KQL. Every new hire can investigate from day one. Observability stops being a specialist skill.

How it works

One workflow. Logs, traces, metrics, infra — explained together.

🧠
ArcIn self-service root cause
“Why is my service slow?” — developers ask ArcIn in plain English and get a specific answer with a specific fix. No SRE required.
↓ 80% SRE interrupts
🔧
Service health in the IDP
Backstage, Port, and custom IDP integrations surface service health, SLO burn rate, and deploy status where developers already work.
📁
Plain English log queries
“Show me errors from my service in the last hour.” No SPL, no KQL. ArcIn queries logs and returns results in seconds.
🚀
Deploy regression alerts
When a developer’s deploy causes a regression, they get a notification with the root cause and fix — before it escalates to an incident.
Applicare — Observability for Devs⬤ Live
SRE escalations
↓80%
vs last quarter
Self-service
4 today
devs resolved own incidents
Time to root cause
<60s
no SRE involvement
Log query time
<2s
plain English · ArcIn
🧠 ArcIn: Developer resolved own incident: asked ArcIn “Why is my checkout-svc slow?” — got root cause, fix, and IntelliTune remediation option. Resolved in 4 minutes. No SRE paged.
What’s covered

Key capabilities — built for the engineer who owns the code.

🧠
ArcIn for Developers
Natural language root cause. No observability expertise required.
🏗️
IDP Integration
Service health in Backstage, Port, or your custom IDP.
📁
Log Intelligence
Plain English log queries via ArcIn. No query language needed.
📡
Trace Explorer
Distributed traces with entity context. Click from trace to root cause.
🚀
Deploy Feedback
Instant regression feedback on every deploy. Fix before it escalates.
📜
SLO Dashboards
Auto-generated SLOs with error budget burn rate — no configuration.
Anatomy of an incident

A slow SQL query, caught and fixed by the developer who wrote it.

T+0s · DETECTION

p99 latency on checkout-svc /checkout starts to climb — 340ms over the cohort baseline. IntelliSense flags the regression before a single customer support ticket arrives. The on-call developer sees it surface in their service’s ArcIn panel in their IDP.

T+15s · INVESTIGATION

The developer asks ArcIn: “why is checkout-svc slow?” ArcIn returns: SQL query in OrderRepository.findRecentOrders() · 2.8s avg · up from 142ms last week. No SPL, no PromQL, no dashboard hunting.

T+34s · ATTRIBUTION

The developer clicks the trace ID. IntelliTrace surfaces the waterfall and the cause: the SELECT scans 1.2M rows because commit a47f9d2 (their own, two days ago) introduced a schema migration that dropped an index. ArcIn explains the chain in plain English.

T+47s · RESOLUTION

IntelliTune drafts the fix — re-add the index on (status, created_at) — and opens PR #4831. The developer reviews it in their IDE, merges, and the deploy ships. The SRE was never paged. The customer never noticed.

Unified observability

Logs, traces, metrics, infrastructure, databases — explained as one workflow.

Most observability tools give you three dashboards and a Slack channel. Applicare gives you one causal graph — every log line linked to the trace that produced it, every span linked to the metric that crossed threshold, every metric anomaly linked to the deploy and the host responsible.
Traces
Every request followed across services, queries, and cloud hops — with method-level timing and span-to-commit attribution.
Logs
Every log line carries its trace ID, service, host, and deploy. Plain-English search via ArcIn — no query language to learn.
Metrics
IntelliSense behavioral baselines per entity, per region, per time-of-week — no threshold rules to maintain.
Infrastructure
Host, container, and Kubernetes events stitched into the request graph. Pod evictions surface alongside the requests they killed.
Databases
SQL and NoSQL queries appear as first-class spans — with parameterized query text, execution plan, and row counts.
Digital experience
A slow user-facing page links directly to the backend trace that caused it. Frontend complaint to backend cause in seconds.
ArcIn AI

Plain-English observability. For every engineer, not just the specialists.

💬
Ask in your own words
“why is checkout-svc slow today?” — ArcIn answers with the offending service, span, log line, and commit attached. No SPL, KQL, PromQL, or LogQL.
🔎
Causal answers, not correlation
IntelliTrace queries the causal entity graph — not a statistical lookup. The answer is which thing caused the other, not just which things happened together.
📝
Investigation memory
When the same incident shape repeats, ArcIn remembers. Past cause, past fix, past responder — surfaced at the start, not after another hour of investigation.
From answer to fix
When ArcIn identifies a known pattern, IntelliTune drafts the remediation as a PR — assigned to the responsible engineer, ready for review.
Developer workflow

Observability where you already work.

In your IDE
ArcIn sidebar in VS Code & JetBrains
Your service’s recent errors, slow spans, and trace patterns appear next to the code you’re writing. Ask ArcIn questions without leaving the editor.
In your PR
Trace regressions caught at review time
When your PR ships to staging, ArcIn comments on the spans that regressed compared to baseline. Catch the slow query before it merges, not after it pages someone.
In your IDP
Backstage, Port & custom IDPs
Service health, ArcIn answers, and IntelliTrace explanations surface next to your service catalog. No tool-switching to find out if your service is healthy.
On-call
Pages with the answer already attached
The PagerDuty incident links to ArcIn’s plain-English explanation — you see the likely cause before you open a single dashboard. The 2 AM page becomes a 2 AM acknowledgment.
CI/CD & release confidence

Every deploy, observed. Every regression, caught in flight.

🚀
Deploy-aware everything
Every span, log line, and metric tagged with its deploy ID and commit hash. Span-level diffs between versions surface automatically.
Sub-60-second regression detection
IntelliSense baselines deploy KPIs per service. Bad releases caught mid-rollout — before they reach all users, before the on-call rotation hears about it.
Policy-gated auto-rollback
When a deploy fails its release SLO, IntelliTune queues a rollback through your existing CD pipeline — behind your existing approval rules.
📊
Pre-built DORA metrics
Deployment frequency, lead time, change failure rate, and MTTR — computed automatically per team, ready for retros and quarterly reviews.
For the buying committee

One platform. Four audiences.

For Developers
Find the bug. Fix the bug. Ship the fix.
Debug your own service without the relay race to SRE. ArcIn answers; you ship. No specialist intermediary, no waiting in a queue.
For Platform Engineering
Embed observability in your IDP
Backstage, Port, and custom IDPs are first-class integration targets. Service health where your developers already work — not in another tool.
For SRE & DevOps
Focus on platform reliability
Developers handle their own service incidents. SRE handles the platform that runs them. The 2 AM page about somebody else’s null check goes away.
For Engineering Leaders
Onboard faster. Escalate less.
Observability stops being a specialist skill. New hires investigate from day one. SRE escalation rates drop 80%. DORA metrics improve quarter over quarter.
Business outcomes

Measurable value. Across the engineering org.

Faster debugging
Self-service plain-English investigation. No SRE handoff. The developer who wrote the code is the one who fixes it — with the full causal chain attached.
Reduced MTTR
Customers report MTTR drops of 90–96% across mobile banking, digital ticketing, and IT services. Documented outcomes below.
Improved release quality
Sub-60-second regression detection. Auto-rollback behind your policy gates. Bad releases caught mid-rollout, not after they hit all users.
Better collaboration
Developers, SRE, Platform Engineering, and Product share one causal view. End the “works on my machine” Slack thread. Start the “ship the fix” PR.
Architecture

How Applicare delivers developer-first observability.

01
Open ingestion
OpenTelemetry-native. Accept OTLP traces, OTLP logs, and OTLP metrics from any SDK or Collector. Bring your existing instrumentation as-is.
02
Streaming pipeline at scale
10M+ spans per minute and 1M+ log lines per second — without head-based sampling. The rare trace you need to debug is always there.
03
Causal entity graph
Every signal joined to the service, host, container, deploy, log line, and commit it came from. This is the graph IntelliTrace queries for causal inference.
04
AI reasoning layer
ArcIn handles natural-language queries. IntelliSense surfaces anomalies. IntelliTrace identifies causal root cause. IntelliTune drafts the fix as a PR.
05
Surfaces where developers work
IDE plugins (VS Code, JetBrains), IDP plugins (Backstage, Port), PR comments, and pager-attached explanations — one platform, surfaced in every tool a developer already uses.
Supported technologies

Bring your stack as-is. Open standards. No lock-in.

Languages
Java · Python · Go · Node.js · .NET · Ruby · PHP · C++
Frameworks
Spring Boot · FastAPI · Django · Express · Rails · ASP.NET · gRPC · GraphQL
Cloud platforms
AWS · Azure · GCP · Hybrid · On-premises · Multi-cluster · Multi-region
Containers & orchestration
Kubernetes · Docker · ECS · Fargate · Istio · Linkerd · Consul Connect
IDE & IDP integrations
VS Code · JetBrains · Backstage · Port · custom IDPs · GitHub · GitLab
Standards
OpenTelemetry native · OTLP/gRPC · OTLP/HTTP · W3C Trace Context · OpenSearch query API
Proven in production

Self-service observability at enterprise scale. Real customers. Real outcomes.

Aerospace · Mexico
AeroMexico
4.5h → 11min
Checkout MTTR cut 96%. Developers diagnosed their own services without escalation — ArcIn answered “what just broke?” before SRE was paged.
Banking · Asia
Leading Private Bank
3.2h → 18min
Mobile banking MTTR dropped 91% in the first month. Span-to-commit attribution let developers fix their own services — without the 3 AM escalation bridge.
IT services · Global
NTT DATA
80% ↓
On-call pages reduced 80%. Developers caught regressions in their own PRs — SRE handled the platform, not somebody else’s null check.
See all customer stories →
Why Applicare

Plain-English. Causal. Developer-first.

  Traditional handoff model Bring-your-own-dashboards Applicare
Who investigatesWait for SRE on-callEngineer who knows the toolsEvery developer, on day one
Query languageSPL / PromQL / LogQLMultiple per toolPlain English (ArcIn)
Tool count3–5 dashboards3–5 dashboardsOne workflow
Time to root causeHoursMinutes (if skilled)<60s (any engineer)
Cause attributionMulti-tool stitchingManualService → span → commit → author
RemediationPage someoneFix it yourselfIntelliTune drafts the fix
Common questions

Frequently asked.

Do I need to instrument differently for ArcIn to work?+

No. Applicare accepts standard OpenTelemetry traces, logs, and metrics. If you’ve instrumented with OpenTelemetry SDKs, point your Collector at Applicare — ArcIn understands the data immediately. Auto-instrumentation is available for services that haven’t been instrumented yet.

Can ArcIn answer questions about services I don’t own?+

Permissions are configurable per service, per team. Developers see their own services by default; cross-team visibility is granted via RBAC. ArcIn can investigate downstream services that affect yours — without exposing source code or sensitive log fields.

How does Applicare integrate with my IDP (Backstage, Port)?+

Applicare ships plugins for Backstage and Port that surface ArcIn answers, service health, and IntelliTrace explanations next to your service catalog. Custom IDPs are supported via a REST API and embeddable widgets.

Does it work with my existing OpenTelemetry setup?+

Yes. Applicare is OpenTelemetry-native. Your existing Collectors, processors, and exporters continue to work — just add Applicare as a destination. No proprietary agents, no parallel instrumentation.

Can I see release impact on metrics I already care about?+

Yes. Every deploy is tagged at the span, log, and metric level. Release-aware dashboards show before/after across whichever KPIs matter to your team — latency, error rate, conversion, or custom business metrics.

How does this affect on-call rotation?+

Most customers report 80% fewer SRE escalations once developers can self-diagnose. The rotation rebalances toward platform reliability (which SRE owns) instead of service debugging (which the responsible developer owns). The 2 AM page becomes the 2 AM acknowledgment.

See Applicare Observability for Developers on your environment.
30 minutes. Read-only access. No prep required.
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