GCE Machine Family Selection Guide
Decision framework for choosing E2, N2, C3, M3, Tau T2D, or GPU families — with workload profiling templates and cost comparison in INR.
Request the Guide →What is Google Compute Engine (GCE)?
Google Compute Engine (GCE) is Google Cloud's infrastructure-as-a-service offering — virtual machines running on Google's global private fibre network. GCE provides configurable VM types (E2, N2, C3, M3, Tau T2D, GPU), Managed Instance Groups for autoscaling and self-healing, sole-tenant nodes for physical isolation, custom machine types for exact vCPU/memory sizing, multiple persistent disk tiers, Spot VMs for up to 91% cost savings, and Committed Use Discounts for long-term commitments. Available in India via asia-south1 (Mumbai) and asia-south2 (Delhi).
- Live migration — zero-downtime host maintenance
- Per-second billing with sustained use discounts
- 99.99% SLA with multi-zone Managed Instance Groups
- Integrates with GKE, Cloud Run, Cloud SQL, and BigQuery
Why Choose PrecisionTech for Compute Engine?
PrecisionTech is an Authorized Google Cloud Partner designing and managing Compute Engine workloads in India — from architecture review and MIG deployment through CUD procurement, Spot VM optimization, and 24×7 managed operations. We also advise when workloads belong on GKE (container orchestration) or Cloud Run (serverless containers) instead of raw VMs — ensuring the right compute layer for every application.
- Authorized Google Cloud Partner + Google Workspace Partner
- 500+ Compute Engine deployments managed
- ISO 9001, ISO 27001, CMMI Level 3
- Typical cost savings: 20–45% within 60 days
Compute Engine Features — Complete Capability Reference
Every GCE capability PrecisionTech designs, deploys, and manages
| Feature | Description | Best For |
|---|---|---|
| VM Instance Types | E2 (cost-optimized), N2/N2D (balanced), C3/C3D (compute), M3 (memory), Tau T2D (scale-out), custom shapes | Matching workload CPU/memory/I/O profile to optimal family |
| Managed Instance Groups | Autoscaling, self-healing, rolling updates, multi-zone distribution, load balancer integration | Production web/app tiers, stateless services, batch workers |
| Sole-Tenant Nodes | Dedicated physical servers — no other customer VMs on same hardware | Compliance isolation, per-core licensing (Oracle, Windows), latency-sensitive apps |
| GPU Instances | NVIDIA T4, L4, A100, H100 attached to a2/a3/g2 machine types with NVLink | ML training, inference, rendering, video transcoding, HPC |
| Persistent Disks | pd-standard, pd-balanced, pd-ssd, pd-extreme, Hyperdisk — live resize, regional replication | Boot volumes, databases, shared file systems via NFS on GCE |
| Local SSD | High-throughput ephemeral storage attached directly to VM | Scratch space for ML training, caching, temp databases |
| Spot VMs | Preemptible capacity at up to 91% discount, 30-second termination notice | Batch processing, CI/CD, rendering, fault-tolerant workers |
| Committed Use Discounts | 1-year or 3-year vCPU/memory or spend commitments for 37–57% discount | Stable baseline workloads after 2–4 weeks usage profiling |
Managed Instance Groups (MIGs)
MIGs are PrecisionTech's default pattern for production GCE deployments. Configure autoscaling policies based on CPU, memory, load balancer capacity, or custom Cloud Monitoring metrics. Self-healing recreates failed VMs automatically. Rolling updates deploy new OS images with zero downtime. Regional MIGs distribute across Mumbai and Delhi zones for 99.99% SLA.
Custom Machine Types
Stop paying for unused vCPUs and RAM. Custom machine types let you specify exact vCPU count and memory — ideal after lift-and-shift migrations that preserved on-premises sizing. PrecisionTech typically saves clients 15–30% by rightsizing to custom E2 or N2 shapes versus default n2-standard presets.
GPU & Sole-Tenant
GPU clusters for AI/ML: a2-highgpu-8g with A100 for training, g2 with L4 for inference, T4 for cost-effective batch inference. Sole-tenant nodes for regulated workloads requiring physical hardware isolation — BFSI, healthcare, and per-core licensed software on Windows Server or Oracle.
When to Use GKE or Cloud Run Instead of GCE
Not every workload belongs on raw VMs. PrecisionTech recommends the right compute layer:
Compute Engine — legacy apps, licensed software (Oracle, SAP),
Windows Server workloads, persistent local state, full OS control.
GKE (Google Kubernetes Engine) — containerized microservices,
complex orchestration, service mesh, multi-container deployments. Google invented Kubernetes.
Cloud Run — stateless HTTP services, event-driven functions,
scales to zero, pay-per-request. No VM management. Ideal for APIs and background jobs.
Compute Engine in GCP India Regions — Low Latency & Data Residency
asia-south1 — Mumbai (2017)
- 3 Availability Zones — primary GCE region for Indian production workloads
- Full machine family availability: E2, N2, C3, M3, Tau T2D, A2/A3 GPU
- Cloud Interconnect POP — dedicated 10/100 Gbps private connectivity
- Regional persistent disks and regional MIGs for HA
- Latency: 5–15 ms to Western & Central India
asia-south2 — Delhi (2021)
- 3 Availability Zones — DR pair and North India latency optimization
- Growing GCE catalogue — all general-purpose and compute-optimized families
- Cross-region MIG failover and snapshot replication target
- Cloud Interconnect — Delhi POP available
- Latency: 5–10 ms to Northern India
PrecisionTech deploys production GCE in asia-south1 with DR replicas in asia-south2. Organization Policy can restrict VM creation to India regions for DPDP Act 2023 compliance.
Compute Engine Use Cases — Industries We Serve
E-Commerce & Retail Platforms
Regional MIGs with HTTP(S) Load Balancing and Cloud CDN for flash-sale traffic spikes. Autoscaler adds capacity in seconds during Diwali and Big Billion Day events. Spot VM pools for catalog indexing and recommendation batch jobs at 60% lower cost.
Free Review →SAP & Enterprise ERP
Memory-optimized M3 instances for SAP HANA, N2 VMs for application servers, and regional persistent disks for /sapmnt. Sole-tenant nodes when SAP licensing requires dedicated hardware. Cross-region DR between Mumbai and Delhi.
Free Review →AI/ML Training & Inference
GPU clusters with a2-highgpu-8g (A100) for model training, g2 (L4) for inference, and Spot VM preemption handling with checkpoint saves. Local SSD scratch disks for dataset staging. Integration with Vertex AI for MLOps pipelines.
Free Review →Financial Services & Trading
Sole-tenant nodes for physical isolation, C3 compute-optimized VMs for low-latency trading engines, and Shielded VM with secure boot for compliance. Multi-zone MIGs with 99.99% SLA for payment processing tiers.
Free Review →Media & Video Processing
GPU-enabled VMs (T4, L4) for video transcoding pipelines. Spot VM fleets for batch rendering with automatic preemption recovery. Cloud Storage integration for input/output with high-throughput persistent disks for temp processing.
Free Review →Dev/Test & CI/CD
Spot VM pools for Cloud Build workers and test environments — spin up on demand, terminate when done. Custom E2 machine types sized for each pipeline stage. Preemptible capacity at 91% discount with MIG auto-replacement on reclamation.
Free Review →Why PrecisionTech for Compute Engine vs. Self-Managed GCE
| Capability | PrecisionTech | Self-Managed | Generic Vendor |
|---|---|---|---|
| Authorized Google Cloud Partner | Yes | No | May not be |
| Free Architecture Review | Included | N/A | Extra cost |
| MIG + Load Balancer Design | Expert | Learning curve | Limited |
| Custom Machine Type Rightsizing | Included | Manual effort | Rarely |
| CUD Procurement & Optimization | Included | Complex | Extra cost |
| Spot VM Pool with Preemption Handling | Included | Risky | Limited |
| GPU Cluster Design (A100/H100/L4) | Expert | Specialist needed | Rare |
| Sole-Tenant for Compliance/Licensing | Yes | Complex setup | Rarely |
| OS Patching & Snapshot Management | 24×7 | Your team | Varies |
| Cloud Monitoring & Alerting | Configured | DIY setup | Basic |
| GKE / Cloud Run Advisory | Included | Separate skill | Rarely |
| India support in India | Yes | Yes | Varies |
PrecisionTech Compute Engine Deployment — 4 Phases
1
Review
Free architecture review. Workload profiling, machine family selection, disk type recommendation, and GCE vs GKE vs Cloud Run decision. Deliverable: architecture diagram + cost estimate in 3 business days.
2
Deploy
Provision VMs or MIGs in asia-south1/asia-south2 via Terraform IaC. Configure load balancers, health checks, autoscaling, persistent disks, OS Login, Shielded VM, and VPC firewall rules.
3
Optimize
Rightsize with Recommender API. Procure Committed Use Discounts. Configure Spot VM pools. Implement snapshot schedules and disk lifecycle cleanup. Typical savings: 20–45%.
4
Manage
24×7 Cloud Monitoring and alerting. OS patching, backup management, incident response per SLA, monthly cost and performance reports, and quarterly Well-Architected Reviews.
What Clients Say About PrecisionTech Compute Engine Services
Rated 4.8 / 5 from 500+ Compute Engine deployments across India
4.8
★★★★★
500+ verified compute reviews
★★★★★"PrecisionTech redesigned our monolithic backend on Compute Engine with Managed Instance Groups and HTTP(S) Load Balancing — peak traffic handling improved 7x during our Diwali sale. Autoscaler launched 35 n2-standard-8 instances in under 90 seconds and scaled back overnight. Mixing Spot VMs for batch jobs cut our compute bill 41% without touching production On-Demand capacity."
★★★★★"We were running oversized n1 instances 24×7 in asia-south1. PrecisionTech rightsized us to e2-custom machine types with predictive autoscaling and 1-year Committed Use Discounts for baseline capacity. Monthly GCE spend dropped 48% while P99 latency improved. They also pointed our stateless API tier toward Cloud Run — a path we would never have found alone."
★★★★★"PrecisionTech provisioned our GPU training cluster — a2-highgpu-8g nodes with NVLink, attached Local SSD scratch disks, and a MIG for inference on T4 GPUs. Sole-tenant nodes isolate our regulated healthcare inference workload from noisy neighbours. CUD procurement and Spot preemption handling saved us ₹6 lakh per month versus our initial self-managed setup."
Reviews represent actual client feedback from PrecisionTech Compute Engine engagements. Names shortened for privacy.
Need a Compute Engine architecture review ?
Free Architecture Review Contact Compute ExpertSupport hours: 11 AM–5 PM, Mon–Fri (excl. holidays)
Compute Engine Knowledge & Resources
Guides and best practices — curated by PrecisionTech's Google Cloud-certified compute architects.
Managed Instance Group Architecture Blueprint
Reference architecture for regional MIGs with HTTP(S) Load Balancing, autoscaling policies, health checks, and rolling update configuration.
Download Blueprint →Spot VM Cost Optimization Playbook
How to build fault-tolerant Spot VM pools with MIG auto-replacement, checkpoint saves, and mixed Spot + On-Demand architectures for 40–60% savings.
Get the Playbook →Committed Use Discount Procurement Guide
When to buy 1-year vs 3-year CUDs, resource-based vs spend-based commitments, and how to avoid over-commitment with usage profiling.
Request the Guide →GCE vs GKE vs Cloud Run Decision Matrix
When to use raw VMs, managed Kubernetes, or serverless containers — with migration paths from monolith to microservices to serverless.
Get the Matrix →GPU Cluster Design for AI/ML on GCP
Architecture patterns for training (A100/H100) and inference (T4/L4) workloads — Local SSD staging, Spot training pools, and Vertex AI integration.
Request the Guide →Explore related Google Cloud solutions from PrecisionTech:
Google Cloud Platform — Overview
Complete GCP services portfolio — migration, Compute Engine, BigQuery, Vertex AI, GKE, Cloud Run, security, cost optimization, and 24×7 managed operations. Authorized Google Cloud Partner + Google Workspace Partner.
Learn more →GCP Cloud Migration
ADAPT methodology, Migrate to Virtual Machines, Database Migration Service, Transfer Appliance, and Landing Zone setup. Move your on-premises or multi-cloud estate to GCP with zero data loss.
Learn more →GCP Compute Engine
VM provisioning, Managed Instance Groups, sole-tenant nodes, GPU instances, custom machine types, persistent disks, Spot VMs, and Committed Use Discounts — the page you are viewing.
Learn more →GCP Storage & BigQuery
Cloud Storage data lakes, dual-region buckets, BigQuery analytics, and Looker Studio dashboards. Attach high-throughput persistent disks and Local SSD to Compute Engine for data-intensive workloads.
Learn more →GCP Databases
Cloud SQL and AlloyDB pair naturally with Compute Engine application tiers. Multi-AZ HA, read replicas, and automated backups — managed database backends for your GCE workloads.
Learn more →GCP Security & IAM
OS Login, Shielded VM, VPC firewall rules, Cloud Armor on load-balanced GCE backends, and IAM least-privilege for service accounts. Secure every Compute Engine deployment.
Learn more →GCP Cost Optimization
CUD procurement, Spot VM pools, custom machine type rightsizing, and sustained use discount tracking for Compute Engine. Reduce GCE spend 20–45% without sacrificing performance.
Learn more →GCP Consulting & Architecture
Well-Architected Reviews, MIG and load balancer design, GPU cluster architecture, and hybrid GCE + GKE + Cloud Run strategy from Google Cloud-certified architects.
Learn more →Amazon AWS Cloud Services
Evaluating EC2 vs Compute Engine? PrecisionTech partners with both AWS and Google Cloud — we provide unbiased compute platform comparison and migration paths between clouds.
Learn more →Frequently Asked Questions — GCP Compute Engine
Everything you need to know about Google Compute Engine and how PrecisionTech designs and manages GCE workloads .
1 What is Google Compute Engine (GCE)?
Google Compute Engine (GCE) is Google Cloud's infrastructure-as-a-service offering — virtual machines running on Google's global fibre network with the same infrastructure that powers Google Search and YouTube. GCE provides: configurable VM types (general-purpose, compute-optimized, memory-optimized, GPU, sole-tenant); persistent and local SSD storage; global VPC networking; live migration (zero-downtime host maintenance); and per-second billing. Available in India via asia-south1 (Mumbai) and asia-south2 (Delhi) for low latency and DPDP Act data residency.
2 What Compute Engine machine families should I choose?
Google offers purpose-built machine families: E2 — cost-optimized general purpose, best price-performance for most workloads; N2/N2D — balanced performance with up to 128 vCPUs, N2D uses AMD EPYC; C3/C3D — compute-optimized for HPC, gaming, and batch processing; M3 — memory-optimized up to 12 TB RAM for SAP HANA and in-memory databases; Tau T2D — scale-out workloads with best per-core price; A2/A3 — GPU instances (NVIDIA A100, H100, L4, T4) for AI/ML training and inference. PrecisionTech recommends machine families based on actual workload profiling during our free architecture review.
3 What are custom machine types on Compute Engine?
Custom machine types let you configure exact vCPU and memory combinations instead of choosing predefined shapes. Select any vCPU count (1–96 for N2, up to 192 for M3) and memory from 1 GB up to 6.5 GB per vCPU (or more for memory-optimized). This eliminates paying for unused CPU or RAM — a common waste after lift-and-shift migrations that preserve on-premises sizing. Custom types are available on E2, N2, N2D, and N1 families. PrecisionTech typically saves clients 15–30% by rightsizing to custom shapes versus default n1-standard or n2-standard presets.
4 What are Managed Instance Groups (MIGs) and why use them?
Managed Instance Groups (MIGs) are collections of identical Compute Engine VMs managed as a single unit. Benefits: Autoscaling — add/remove VMs based on CPU, memory, load balancer capacity, or custom Cloud Monitoring metrics; Self-healing — automatically recreates failed VMs; Rolling updates — deploy new OS images or application versions with zero downtime; Multi-zone HA — distribute VMs across zones within a region for 99.99% SLA; Load balancing — integrate with HTTP(S), TCP/SSL, or internal load balancers. PrecisionTech deploys MIGs as the standard pattern for production web and application tiers on GCP.
5 What are sole-tenant nodes on Compute Engine?
Sole-tenant nodes are physical Compute Engine servers dedicated exclusively to your project — no other customer's VMs share the hardware. Use cases: Compliance — meet regulatory requirements for physical isolation (BFSI, healthcare, government); Licensing — per-core/per-socket software licenses (Windows Server, Oracle, SQL Server) where multi-tenant VMs violate license terms; Performance — eliminate noisy-neighbour effects for latency-sensitive workloads. You pay for the entire physical node and place VMs on it with full control over maintenance windows. PrecisionTech configures sole-tenant for regulated Indian clients requiring hardware-level isolation.
6 What GPU options are available on Compute Engine?
GCP offers NVIDIA GPUs attached to Compute Engine VMs: T4 — inference, video transcoding, light training (cost-effective); L4 — generative AI inference, graphics; A100 (a2) — large-scale ML training with NVLink; H100 (a3) — cutting-edge LLM training and inference; V100/P100/P4/K80 — legacy training workloads. GPUs attach to specific machine types (e.g., n1-standard with T4, a2-highgpu-8g with A100). Local SSD scratch disks provide high-throughput temporary storage for training datasets. PrecisionTech designs GPU clusters with MIG-based inference tiers and Spot VM training pools for cost efficiency.
7 What persistent disk types does Compute Engine offer?
GCE persistent disks are network-attached block storage: pd-standard — HDD-backed, lowest cost for sequential reads (backups, logs); pd-balanced — SSD-backed, default for most workloads, balanced price-performance; pd-ssd — high-IOPS SSD for databases and latency-sensitive apps; pd-extreme — highest IOPS/throughput for demanding databases; Hyperdisk — next-gen block storage with independently configurable IOPS and throughput. Disks can be resized live without VM restart. Regional persistent disks replicate synchronously across two zones for HA. PrecisionTech selects disk types based on I/O profiling, not guesswork.
8 What are Spot VMs and how do they reduce costs?
Spot VMs (formerly preemptible VMs) are excess Compute Engine capacity offered at up to 91% discount versus On-Demand pricing. Google can reclaim Spot VMs with 30 seconds notice when capacity is needed. Best for: batch processing, rendering, CI/CD build agents, data analytics, ML training with checkpointing, and stateless worker pools. PrecisionTech builds Spot VM pools with Managed Instance Groups that automatically replace preempted instances, combined with On-Demand baseline capacity for production-critical workloads. Typical savings: 40–60% on compute-heavy batch operations.
9 What are Committed Use Discounts (CUDs) on Compute Engine?
Committed Use Discounts (CUDs) provide 37–57% discount on Compute Engine in exchange for a 1-year or 3-year commitment to a specific vCPU and memory amount in a region. Types: Resource-based CUDs — commit to vCPU/RAM amounts, apply across any VM shape in the region; Spend-based CUDs — commit to a dollar amount per hour, flexible across Compute Engine, GKE, and Cloud Run. Sustained Use Discounts (automatic, up to 30%) stack with CUDs for additional savings. PrecisionTech analyzes 2–4 weeks of usage data before recommending optimal CUD purchases — avoiding over-commitment.
10 How does Compute Engine compare to Cloud Run and GKE?
Compute Engine — full VM control, any OS/software, ideal for legacy apps, licensed software, and workloads needing persistent local state. Cloud Run — serverless containers, scales to zero, pay-per-request, best for stateless HTTP services and event-driven functions — no VM management. GKE (Google Kubernetes Engine) — managed Kubernetes for containerized microservices needing orchestration, service mesh, and complex deployment patterns. PrecisionTech often deploys hybrid architectures: GCE for databases and licensed apps, GKE for microservices, Cloud Run for APIs and background jobs. We recommend the right compute layer per workload during architecture review.
11 What is live migration on Compute Engine?
Live migration is a Google Cloud differentiator — when underlying physical hardware needs maintenance (patching, upgrades, failures), GCE automatically migrates your running VM to another host with zero downtime and zero performance impact. Your application keeps running throughout. This eliminates the planned-maintenance reboots required on other cloud providers. Live migration applies to standard VMs; sole-tenant nodes give you control over maintenance scheduling instead. Combined with MIG self-healing, this delivers high availability without complex failover architectures for many workloads.
12 How does PrecisionTech manage Compute Engine security?
PrecisionTech implements GCE security best practices: OS Login — IAM-based SSH key management, no shared keys; Shielded VM — secure boot, vTPM, integrity monitoring; VPC firewall rules — least-privilege network access, no 0.0.0.0/0 on sensitive ports; Private Google Access — reach Google APIs without public IPs; Service accounts — per-VM identity with minimal IAM roles; Confidential VMs — AMD SEV or Intel TDX encryption in use for sensitive data; Cloud Armor — DDoS protection on load-balanced GCE backends. Monthly security posture reviews included in managed services.
13 What load balancing options work with Compute Engine?
Google Cloud Load Balancing integrates natively with GCE and MIGs: External HTTP(S) — global anycast, SSL termination, CDN integration via Cloud CDN; External TCP/SSL Proxy — non-HTTP TCP traffic with global load balancing; Internal HTTP(S) — load balance within VPC across zones; Internal TCP/UDP — internal service discovery and load distribution; Network Load Balancing — pass-through L4 for ultra-low latency. All support health checks, autoscaling integration, and cross-region failover. PrecisionTech designs load-balanced GCE architectures with 99.99% availability targets.
14 Can I run Windows Server on Compute Engine?
Yes. Compute Engine supports Windows Server 2016, 2019, 2022, and 2025 with per-core licensing (Bring Your Own License or pay-as-you-go via Google). Windows VMs support Active Directory domain join, SQL Server, IIS, .NET applications, and Remote Desktop. PrecisionTech deploys Windows GCE workloads with: sole-tenant nodes when licensing requires dedicated hardware; Managed Instance Groups for IIS web farms; and Cloud Backup for VM snapshot schedules. Common use cases: .NET enterprise apps, SQL Server databases, Active Directory domain controllers, and Remote Desktop Services.
15 How does PrecisionTech optimize Compute Engine costs?
PrecisionTech's cost optimization program includes: (1) Rightsizing — Recommender API + custom profiling to match VM shape to actual utilization; (2) Custom machine types — eliminate wasted vCPU/RAM; (3) CUD procurement — 1-year/3-year commitments for stable baselines; (4) Spot VM pools — batch and dev/test on preemptible capacity; (5) Disk optimization — pd-balanced instead of pd-ssd where I/O allows; snapshot lifecycle cleanup; (6) Idle resource cleanup — stop/delete unused VMs, unattached disks; (7) Monthly reporting — billing breakdown by project, label, and service. Typical savings: 20–45% within 60 days.
16 What monitoring and alerting does PrecisionTech provide for GCE?
PrecisionTech configures Cloud Monitoring for every managed GCE deployment: CPU, memory, disk I/O, and network metrics per VM and MIG; custom application metrics via OpenTelemetry or Ops Agent; uptime checks on HTTP/TCP endpoints; log-based metrics from Cloud Logging; alerting policies with PagerDuty, email, or SMS notification; and dashboards for operations and executive visibility. Managed services include 24×7 alert response per SLA — our India-based NOC investigates and resolves GCE incidents during business hours (11 AM–5 PM Mon–Fri) with emergency escalation paths for critical production outages.
17 What is the Compute Engine SLA?
Google provides a 99.99% monthly uptime SLA for VMs in a Managed Instance Group spread across two or more zones in a region. Single-zone VMs carry a 99.5% SLA. If Google fails to meet the SLA, you receive financial credits (10–50% of monthly charges depending on uptime achieved). PrecisionTech architectures production workloads on multi-zone MIGs with health-checked load balancers to qualify for the 99.99% SLA — and we document the architecture for your own SLA commitments to end customers.
18 How do I migrate existing VMs to Compute Engine?
Primary path: Migrate to Virtual Machines (M2VM) — install replication agent on source servers, continuous block-level replication to GCE, test clone, cutover. Also supported: manual image import (RAW/VMDK/VHD to persistent disk), Terraform import for IaC-managed environments, and containerization to GKE/Cloud Run for cloud-native modernization. PrecisionTech handles the full migration — from Landing Zone setup through M2VM execution to post-migration rightsizing. See our GCP Cloud Migration page for full migration service details.
19 What backup and disaster recovery options exist for GCE?
GCE backup and DR options: Snapshot schedules — automated daily/weekly persistent disk snapshots with cross-region copy to asia-south2; Machine Images — capture full VM configuration (disks, metadata, network) for fast recovery; Cloud Backup for GCE — application-aware backup with granular file-level restore; Regional MIGs — VMs distributed across Mumbai and Delhi zones; Cross-region DR — replicate snapshots and MIG templates to asia-south2 for regional failover. PrecisionTech designs DR architectures with documented RTO/RPO targets and conducts quarterly DR drills.
20 Does PrecisionTech offer managed Compute Engine services?
Yes. PrecisionTech GCP managed compute services include: VM and MIG provisioning and configuration; OS patching and image lifecycle management; Cloud Monitoring and alerting with 24×7 response; backup and snapshot management; cost optimization reviews (CUDs, Spot VMs, rightsizing); security hardening (OS Login, Shielded VM, firewall rules); and monthly executive reports. Engagements start from ₹8,999/month for SMB estates. Contact /contact/ for a free architecture review — we respond within 4 business hours, Monday–Friday 11 AM–5 PM IST (excluding holidays).
21 What India regions are available for Compute Engine?
Google Cloud operates two India regions for Compute Engine: asia-south1 (Mumbai) — 3 zones, launched 2017, primary region for most Indian workloads, full GCE machine family availability including GPU; asia-south2 (Delhi) — 3 zones, launched 2021, ideal DR pair and for North India latency optimization. Both regions support all persistent disk types, Managed Instance Groups, load balancers, and Cloud Interconnect. Organization Policy can restrict deployments to these regions for DPDP Act compliance. PrecisionTech deploys production in asia-south1 with DR replicas in asia-south2 as standard practice.
22 Is PrecisionTech an authorized Google Cloud Partner for Compute Engine?
Yes. PRECISION e-Technologies Pvt Ltd (PrecisionTech.in) is an Authorized Google Cloud Partner and Google Workspace Partner in India. Our team holds Google Cloud Professional Cloud Architect and Professional DevOps Engineer certifications. We design, deploy, and manage Compute Engine workloads for Indian businesses across manufacturing, BFSI, healthcare, e-commerce, and SaaS — with ISO 9001, ISO 27001, and CMMI Level 3 certifications. 30+ years of IT infrastructure experience since 1995.
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