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Every stack.
Fully monitored.

AWS, Azure, GCP, Kubernetes, SAP, ServiceNow, VMware — all correlated in one causal entity graph with ArcIn root cause and IntelliTune auto-remediation.

50+
AWS services
<60s
Root cause
40%
Cost reduction
☁️
Cross-service causal graph
EC2, Lambda, RDS, EKS — one entity graph. Lambda throttles because RDS is saturated because a deploy removed connection pooling: one incident, one answer.
↓ Root cause in <60s
💰
Cost anomaly detection
Spend correlated with traffic and deploys. Rightsizing backed by 30-day actual utilisation.
↓ 40% cloud cost avg
📋
GovCloud & FedRAMP
Full AWS GovCloud monitoring. FedRAMP Authorization in Progress — ITAR, FISMA, CMMC ready.
⚡
Deploy regression detection
Every CodePipeline stage correlated with downstream metrics in 60 seconds.
Book AWS demo →
Applicare — AWS⬤ Live
ALB 5xx Rate
2.4%
api-prod · threshold 1%
RDS Connections
99.6%
aurora-prod · near limit
Lambda
Normal
order-processor · healthy
Cost Variance
+$4.2k
vs last week · spike
🧠 ArcIn: Root cause: deploy #6204 removed RDS Proxy config → connection exhaustion → ALB 5xx cascade. IntelliTune: proxy restored.
30+
Azure services
<60s
Root cause
35%
Cost reduction
🔗
Cross-service entity graph
VMs, AKS, SQL, App Service, Blob, Functions — one causal graph. Incidents show as one root cause, not five alerts.
📊
Azure Cost Intelligence
Spend anomalies correlated with traffic and deploys. Rightsizing backed by 30-day utilisation.
📋
Azure Government
Full Azure Government monitoring. NIST, FedRAMP, CMMC continuously monitored.
⚡
AKS deployment gates
Pod-level regressions detected during rollout.
Book Azure demo →
Applicare — Azure⬤ Live
AKS Pod Health
98.2%
prod · 2 pods restarting
Azure SQL DTU
78%
orders-db · near limit
App Service
Healthy
all instances OK
Blob Cost
+12%
vs baseline
🧠 ArcIn: AKS pod restarts correlated with Azure SQL DTU spike — N+1 query from deploy #5891. IntelliTune: query cache warming.
25+
GCP services
<60s
Root cause
38%
Cost reduction
🔗
Cross-service causal graph
GCE, GKE, BigQuery, Cloud SQL, Pub/Sub, Cloud Run — one entity graph. Root cause traces from frontend to backend.
⎈
GKE Workload Intelligence
Pod health, node auto-provisioning, and deployment regression detection correlated with app performance.
📊
GCP Cost Intelligence
Committed use and sustained use savings. Rightsizing backed by actual workload patterns.
🔗
Multi-cloud correlation
GCP workloads correlated with AWS and Azure dependencies.
Book Google Cloud demo →
Applicare — Google Cloud⬤ Live
GKE Nodes
All healthy
prod-cluster · 12 nodes
BigQuery Slots
94%
analytics · near limit
Cloud SQL
Normal
postgres-prod · healthy
Pub/Sub Backlog
+340k
orders-topic · growing
🧠 ArcIn: Pub/Sub backlog correlated with Cloud SQL exhaustion — deploy #4821 missing pool config. IntelliTune: pool size 20→80.
100%
Pod visibility
<60s
Deploy regression
80%
Page reduction
⎈
Full workload visibility
Every deployment, statefulset, daemonset — health, resource consumption, restart history, and app performance inside each pod.
↓ 80% K8s pages
🚀
Deployment health gates
Every rollout assessed for regression within 60 seconds. Automatic rollback trigger support.
🔗
Service mesh correlation
Istio, Linkerd, Envoy metrics correlated with service performance.
🛡️
Security inline
RBAC misconfigs, privileged containers, and CIS benchmark violations alongside performance data.
Book Kubernetes demo →
Applicare — Kubernetes⬤ Live
Pod Restarts
3
payment-ns · 10min
Node CPU
Normal
12 nodes · healthy
Deploy Health
Degraded
checkout-svc · +340ms
PVC Usage
67%
postgres-data · OK
🧠 ArcIn: Deploy regression: checkout-svc #6205 — p99 +340ms. N+1 in OrderRepository. IntelliTune: rollback triggered. 0 user impact.
99.9%
System uptime
<5min
Regression detection
60%
Ticket reduction
🏢
ABAP & NetWeaver
Work process utilisation, dialog step performance, batch job health, RFC call tracking.
↓ 60% support tickets
💾
HANA intelligence
Memory utilisation, column store health, SQL performance — correlated with SAP application transactions.
🔗
Landscape correlation
ECC, S/4HANA, BW, Solution Manager in one entity graph. RFC dependency mapping.
📊
Business process KPIs
Order-to-cash, procure-to-pay health — alerting when business outcomes degrade.
Book SAP demo →
Applicare — SAP⬤ Live
Dialog Response
1.2s
prod · threshold 2s
HANA Memory
84%
hana-prod · near limit
Batch Jobs
2 failed
night processing
RFC Connections
Normal
200/400 · healthy
🧠 ArcIn: HANA memory pressure → batch failures — missing temp table cleanup. IntelliTune: temp space cleared, jobs requeued.
99.95%
Availability SLA
<2min
Incident enrichment
70%
Resolution reduction
🎫
ITSM workflow health
Queue depth, SLA breach predictions, assignment overload detection — before tickets breach.
↓ 70% resolution time
🔗
Bi-directional integration
ArcIn root cause automatically populates incident records — creates ticket, enriches it, assigns it.
📊
Platform performance
Instance response times, MID server health, discovery job performance.
🔄
Change intelligence
Change records correlated with infrastructure impact. Regressions detected in 60 seconds.
Book ServiceNow demo →
Applicare — ServiceNow⬤ Live
Instance Response
0.8s
prod · SLA 2s · OK
Active Incidents
14
3 P1 · ArcIn enriched
MID Server
All OK
4 servers · healthy
Change Windows
2 open
post-change monitoring
🧠 ArcIn: 3 P1 incidents share root cause: network change CHG0045821 blocking DB replication. ArcIn evidence sent to all records.
100%
VM coverage
<5min
App-to-infra root cause
45%
Rightsizing savings
🖥️
vSphere & ESXi monitoring
VM CPU, memory, storage I/O correlated with application performance. CPU ready time mapped to application latency.
↓ 45% VM cost
💾
vSAN performance
Datastore latency, IOPS, and congestion correlated with VMs experiencing degradation.
🔗
NSX-T network visibility
East-west traffic flows, DFW rule hits, and load balancer health correlated with connectivity issues.
🏗️
Tanzu integration
K8s workloads on Tanzu monitored at both K8s and underlying VM infrastructure layers.
Book VMware demo →
Applicare — VMware⬤ Live
vCenter Health
All OK
12 hosts · no alerts
vSAN Latency
2.1ms
prod-ds · threshold 5ms
VM CPU Ready
8%
checkout-vm · elevated
NSX DFW
Normal
all rules healthy
🧠 ArcIn: checkout-vm CPU ready 8% — contention on esx-04. DRS: migrate to esx-07. IntelliTune: migration initiated.
80+
Auto-instrumented
100%
OTLP compatible
0
Code changes
📡
Native OTLP ingestion
Accepts OTLP over gRPC and HTTP from any OTel SDK, collector, or forwarder. No proprietary agents required.
Zero vendor lock-in
🔧
Auto-instrumentation agent
Zero-code instrumentation for 80+ frameworks — Spring Boot, Django, Express, Rails, FastAPI.
🔗
OTel + entity graph
OTel traces enriched with entity context — every span linked to service entity, deployment, host, and SLO.
📋
Collector distribution
Pre-configured OTel Collector with Applicare exporter. Deploy in 10 minutes.
Book OpenTelemetry demo →
Applicare — OpenTelemetry⬤ Live
OTLP Ingestion
10M/min
All sources · zero sampling
Collector Health
All OK
3 collectors · healthy
Frameworks
80+
Auto-instrumented
Trace Correlation
100%
All spans entity-linked
🧠 ArcIn: OTel trace spike: checkout-svc v2.4 sync HTTP call to inventory-svc without timeout — spans timing out after 30s.
11 min
MTTR (from 4.5h)
80%
Page reduction
<60s
Deploy regression
🚀
Deploy regression detection
Every deploy correlated with downstream metrics in 60 seconds. Bad deploys caught mid-rollout.
↓ MTTR 4.5h → 11min
⚡
IntelliTune auto-remediation
200+ patterns in 400ms within policy gates. 80% of on-call pages never happen.
📊
DORA metrics pre-built
Deployment frequency, change failure rate, MTTR, lead time — pre-built for every team.
🔍
Code-level attribution
Slow spans linked to service class, method, and git commit. Trace to commit in one click.
Book DevOps demo →
Applicare — DevOps⬤ Live
MTTR this week
11 min
↓ from 4.5 hrs
On-call pages
4
↓ 80% vs last month
Deploy #6205
Regression
checkout-svc · +340ms
Auto-remediations
4 today
0 pages fired
🧠 ArcIn: Deploy #6205: N+1 in OrderRepository. IntelliTune: rollback triggered in 380ms. 0 user impact. 0 pages fired.
94.7%
FedRAMP compliance
18 days
ATO prep (from 11wk)
0
Violations at audit
🔒
Continuous compliance monitoring
NIST 800-53, FedRAMP High (authorization in progress), CMMC Level 2, SOC 2 — monitored continuously. Drift flagged immediately.
0 audit surprises
📋
ATO evidence automation
Every control automatically evidenced. ATO packages generated on-demand — not manually assembled.
18-day ATO prep avg
🔧
Auto-remediation of violations
IntelliTune fixes open security groups, unencrypted storage, missing MFA, excessive IAM permissions.
🔍
IAM & privilege analysis
Maps IAM roles and policies. Flags privilege escalation paths and wildcard permissions in real time.
Book DevSecOps demo →
Applicare — DevSecOps⬤ Live
NIST 800-53
94.7%
847/895 controls
CIS Benchmark
9.1/10
7 controls drifted
IAM Violations
3 new
wildcard policies
ATO Evidence
Ready
Full package on-demand
🧠 ArcIn: IAM escalation: 2 role policies grant s3:* without resource scope. ATO evidence updated. IntelliTune rollback queued.
<30s
Query attributed to app
100%
Query plans captured
65%
Incident reduction
🗄️
Query performance intelligence
Slow queries attributed to the exact service and code path. N+1 patterns, missing indexes — with the exact ORM call.
↓ 65% DB incidents
🔗
Connection pool monitoring
Pool saturation detected before exhaustion. Leaks identified by service.
📊
Replication & HA health
Primary/replica lag, failover events — correlated with application read performance.
💰
Cost optimisation
Unused indexes, over-provisioned instances — rightsizing backed by 30-day actuals.
Book Databases demo →
Applicare — Databases⬤ Live
Slow Queries
14/hr
checkout-svc · N+1
Connection Pool
96%
orders-db · near limit
Replication Lag
Normal
0.8s · healthy
DB Cost
Over-prov.
3 instances · rightsizing
🧠 ArcIn: N+1 in checkout-svc: OrderRepository executing 47 SELECTs/request. Fix: eager load on order_items. ↓340ms p99.
1M+
Log lines/sec
100%
Trace-linked logs
0
Query language needed
📂
ArcIn plain English queries
"Show me errors from checkout-svc last hour" — plain English, any language. No SPL, no KQL.
Zero query language
🔗
Trace-linked logs
Every log line linked to its trace. Jump from distributed trace to application logs in one click.
👁️
Anomalous pattern detection
IntelliSense monitors log volume and error patterns per entity. New error types flagged automatically.
⚡
1M+ lines/sec ingestion
No dropping, no sampling. Every log line retained and entity-linked.
Book Log Management demo →
Applicare — Log Management⬤ Live
Ingestion Rate
1M+/sec
Zero dropping
Trace Correlation
100%
All logs entity-linked
Error Rate
+340%
checkout-svc · spike
Query Response
<2s
Plain English queries
🧠 ArcIn: "Errors in checkout-svc last hour" → 4,240 errors, NullPointerException in OrderRepository line 142 — correlated with deploy #6205.