OpsEpoch · AI-native observability

AI that monitors, analyses & fixes your stack

OpsEpoch puts an AI agent on every layer — servers, websites, Kubernetes, logs and APM. It watches continuously, reasons about what broke, and remediates automatically. AI intelligence and assistance, everywhere you operate.

👁️AI Monitor · always watching
🧠AI Analyse · RCA & correlation
AI Fix · auto-remediation
opsepoch / ai-control-plane / overview AI · LIVE 24/7
Uptime
99.98%
p95 latency
142ms
AI auto-fixes
37
request throughput · AI-scored · 24h▲ 8.4%
AI event stream
Log anomaly · error rate spike in paymentsai · debug queued
AI Analyse correlated logs → deploy #a19f4root cause · 92% conf
AI Fix scaled pool & rolled configk8s · auto-remediation
Incident #4821 resolved · MTTR 3mai-verified · healthy
Vendor-agnostic · any hardware, any cloud ⏱️ Sub-minute polling 🔌 50+ exporters & integrations 🛡️ SLA-grade 99.99% coverage
The OpsEpoch loop

One AI loop: Monitor → Analyse → Fix

Every capability in OpsEpoch runs through the same closed AI loop. No dashboards to babysit, no runbooks to memorize — the agent carries the incident from detection to verified recovery.

👁️
01 · Monitor with AI

AI Monitor

Agents watch every metric, log line, trace and endpoint across servers, sites, Kubernetes and APM — learning normal so they catch what static thresholds miss.

🧠
02 · Analyse with AI

AI Analyse

The moment something drifts, the agent correlates signals, logs and recent changes to produce a ranked root-cause analysis with evidence and confidence.

03 · Fix with AI

AI Fix

AI Resolve executes the remediation — scale, restart, roll back, patch — then verifies recovery and closes the incident. You approve only when it matters.

OpsEpoch · Capabilities

Nine AI capability areas, in production

Full-stack coverage — every layer instrumented, every layer intelligent. AI assistance is baked into each area, not bolted on.

LIVE
🖥️

AI Server Monitoring

Node Exporter, system metrics and exporter lifecycle — AI baselines detect drift early.

✦ AI baselining
LIVE
🌐

AI Website Monitoring

Uptime, HTTP status, SSL expiry and latency — with AI anomaly scoring on every check.

✦ AI anomaly scoring
LIVE
☸️

AI Kubernetes Monitoring

Cluster, namespace, pod and node visibility with AI-detected crashloops and pressure.

✦ AI health inference
LIVE
🧾

AI Log Intelligence

Centralized log aggregation with search, correlation and an AI debug system that reads the logs for you.

✦ Intelligent debug
LIVE
🔔

AI Alerting

Critical, Warning & Info tiers with custom templates — AI suppresses noise and groups duplicates.

✦ AI noise reduction
LIVE
🤖

AI Troubleshooting & Automation

AI Chat Resolve, AI Resolve and RCA suggestions — diagnose and fix in one conversation.

✦ Chat Resolve · RCA
LIVE
📊

AI APM Monitoring

AI-based backend execution workflow tracing across services and dependencies.

✦ AI trace analysis
LIVE
🔐

AI Remote Access & Execution

Browser-based SSH and command executor — AI suggests the exact commands to run.

✦ AI-guided actions
LIVE
🧭

AI Dashboards at a Glance

System, Redis, MySQL, daemon services and SystemD — AI surfaces what needs attention first.

✦ AI prioritized views
AI Log Intelligence

Centralized logs, debugged by AI

No more grepping through gigabytes. OpsEpoch aggregates every log stream into one searchable place, then an intelligent AI system reads them — spotting the anomaly, tracing it to the cause, and explaining it in plain English.

  • Unified aggregation — every server, container and service in one stream.
  • Search & correlation — pivot from a metric spike to the exact log lines behind it.
  • AI debug system — the agent reads logs, isolates the error pattern, and proposes the fix.
  • Plain-English root cause — no query language required to understand what broke.
opsepoch · logs · payments-svc · live tail
14:02:11INFOpool acquire ok · size 118/128
14:02:47WARNpool near limit · 127/128
14:02:52ERRORredis: connection pool exhausted
14:02:52ERRORtimeout waiting for connection (890ms)
14:03:01AI ▸correlated 214 errors → deploy #a19f4
AI DEBUGRoot cause: deploy #a19f4 lowered cache TTL, exhausting the Redis pool under load. Suggested fix: raise pool 128→256 and roll back TTL. Applying via AI Resolve…
Datacenter Expertise

Rack to runtime — we cover the whole datacenter

OpsEpoch is built by engineers who run infrastructure for a living. From bare-metal and power to hypervisors, storage fabric and the apps on top — every domain is instrumented, and every domain is watched by AI.

Rack A · Row 3AI monitored
web-01compute
web-02compute
k8s-node-4k8s
db-primarymysql
cache-01redis
storage-sanceph
fw-corenetwork
pdu-ups-apower
🖥️

Bare-Metal & Server Fleets

Hardware health, firmware, disk SMART and out-of-band control across your fleet.

IPMIiLOiDRACNode Exporter
🧱

Virtualization

Hypervisor, VM density, host contention and live-migration visibility.

VMwareKVMProxmoxHyper-V
🌐

Network & Fabric

Switch, router and firewall telemetry, throughput, packet loss and BGP state.

SNMPBGPNetFlowSD-WAN
💾

Storage & Fabric

SAN/NAS capacity, IOPS, RAID health and distributed-storage cluster state.

CephZFSiSCSIRAID

Power, Cooling & Environment

PDU/UPS load, temperature, humidity and airflow — physical-layer early warning.

PDUUPSTempModbus
☸️

Kubernetes & Containers

Cluster, namespace, node and pod health with AI-detected crashloops and pressure.

K8sOpenShiftcontainerdHelm
🗄️

Databases & Cache

Query latency, replication lag, connections and cache pressure across engines.

MySQLPostgreSQLRedisMongo
♻️

Backup, DR & Security

Snapshot success, replication, RTO/RPO tracking and access-audit coverage.

SnapshotsReplicationRTO/RPOAudit
AI Agent Workflow · RCA · Auto-remediation

From anomaly to resolution — the AI agent handles the loop

OpsEpoch doesn't just page a human. Autonomous AI agents detect the anomaly, investigate causality across metrics and logs, generate a root-cause analysis, apply the fix, and verify recovery — with a human in the loop only when it matters.

1🚨

Detect

AI surfaces a metric, log & trace anomaly across the full stack.

2🔎

Investigate

Agent correlates signals, logs, dependencies and recent changes.

3🧠

Analyse · RCA

Ranked root-cause hypotheses with confidence & evidence.

4

AI Fix

Executes remediation — scale, restart, roll back, patch.

5

Verify

Confirms recovery, closes incident, logs the MTTR.

🤖 OpsEpoch · AI Chat Resolve troubleshooting
On-call engineerWhy is checkout latency spiking on node-7?
OpsEpoch AgentReading the logs now — I traced it to a Redis connection pool exhaustion triggered 6m ago after deploy #a19f4. Pool maxed at 128, requests are queuing. Latency p95 jumped 142ms → 890ms.
On-call engineerCan you fix it?
OpsEpoch AgentRunning AI Fix: raising pool to 256 and scaling the worker replica set +2. Rollback is on standby. I'll verify recovery and confirm. ✅ Recovered — p95 back to 138ms, incident closed.
🧠 AI Root Cause Analysis — Incident #4821 generated
🎯
Primary cause · Redis pool exhaustion

Connection pool saturated after deploy #a19f4 changed cache TTL.

AI confidence 92%
🔗
Contributing · Traffic surge

Throughput +34% coincided with a marketing send at 14:02 UTC.

AI confidence 61%
🛠️
AI remediation applied

Pool 128 → 256 · replica set +2 · deploy flagged for review.

✅ AI-verified healthy · MTTR 3m 12s
OpsEpoch · Problems Resolved

What AI-native ops eliminates

Every capability maps to a real operational pain — and the outcome AI delivers.

Servers crash without warning

Fixed by: AI server monitoring + baselining

→ Zero surprise outages

Buried logs, slow debugging

Fixed by: AI Log Intelligence — centralized & auto-debugged

→ Root cause in minutes

Pods crashlooping unnoticed

Fixed by: AI Kubernetes health inference

→ Container reliability

Critical alerts lost in noise

Fixed by: AI-tiered alerts with noise reduction

→ Right person, right time

MTTR is too long

Fixed by: AI Chat Resolve, AI Fix & RCA

→ Faster recovery

Expired SSL & website outages

Fixed by: AI website & SSL monitoring

→ Customer trust protected

Manual, error-prone fixes

Fixed by: AI-guided remote access & execution

→ Less toil, fewer mistakes

Fragmented views, late discovery

Fixed by: AI-prioritized dashboards & APM tracing

→ Single pane of glass
Business Impact

Monitor. Analyse. Fix. All with AI.

9
AI capability areas, all live
24/7
AI coverage & auto-remediation
1
AI platform — one pane of glass
FAQ

Frequently Asked Questions

What's actually covered under OpsEpoch's monitoring?
The nine capability areas shown on the page: servers, websites (uptime, SSL, latency), Kubernetes, centralized logs, tiered alerting, APM/backend traces, remote access & command execution, and unified dashboards — plus deeper datacenter layers (bare-metal, virtualization, network, storage, power/cooling) covered vendor-agnostically with sub-minute polling across 50+ exporters.
What happens when the AI detects an issue — walk me through the process?
It follows the 5-step loop shown in the AI Workflow section: Detect the anomaly across metrics/logs/traces, Investigate by correlating signals and recent changes, produce a ranked root-cause analysis with confidence scores (like the Incident #4821 example — 92% primary cause, 61% contributing factor), apply AI Fix (scale, restart, roll back, patch), then Verify recovery and log the MTTR before closing the incident.
Can I just ask it questions instead of digging through dashboards?
Yes — that's AI Chat Resolve, shown in the page's chat panel. You can ask something like "why is checkout latency spiking on node-7," and the agent reads the logs, explains the root cause in plain English, and can execute the fix conversationally when you confirm.
Does the AI make changes on its own, or do I stay in control?
You stay in control where it counts — the page states "you approve only when it matters." Remediation actions run with a rollback on standby and get verified before the incident is marked closed, so nothing changes silently.
Does OpsEpoch reduce alert noise, or will my team get flooded?
Alerting is tiered into Critical, Warning, and Info with custom templates, and the AI groups duplicates and suppresses noise so the right person sees the right alert at the right time — rather than everything hitting the same channel.
Is there a trial, or how do I get started?
There's no self-serve trial for OpsEpoch — the page's CTAs are "Deploy OpsEpoch" and "Book a live AI walkthrough." The right next step is an AI walkthrough with our team, where we scope your environment and show the AI Monitor → Analyse → Fix loop against scenarios relevant to your stack.

Stop firefighting. Let OpsEpoch's AI run your ops.

Deploy across your servers, sites, Kubernetes, logs and APM — and let AI agents monitor, analyse and fix incidents while you sleep.