Save The Day In The Skills Boost Arcade!

[Yugali]

Arcade Players, your skills have made a real difference — and now, a new challenge awaits!

A fast-growing company is working to scale its cloud infrastructure, but they’re facing a few hurdles:

• They need to strengthen their application security against potential threats.
• Their teams require secure, streamlined access to APIs and services.
• Their databases must handle heavy loads with high availability and resilience.
• And they’re looking for smart ways to keep cloud costs optimized as they grow.

The Challenge:

Which Google Cloud tools and strategies should they use to:

• Enhance security for applications and APIs,
• Manage service accounts and encryption keys securely,
• Build a scalable and durable database backend,
• Monitor Kubernetes clusters effectively,
• And optimize cloud storage costs?

Think about solutions that involve Cloud Armor, Service Accounts, Cloud KMS, Cloud Spanner, GKE, Prometheus, Cloud Storage, and APIs in Google Cloud.
Share your best approach in the comments — the most insightful responses will be featured in our next community post!

Before we wrap up, let’s celebrate the top contributors from our last Save the Day Challenge.

A Big Shoutout To:
1) Killwish
2) seankhurana
3) Mannu2107
4) Nandini4

See You In The Cloud!

[chaitanyadani06]

Here's a comprehensive approach to addressing these requirements using Google Cloud tools:

Security for Applications and APIs:
Cloud Armor provides DDoS protection and Web Application Firewall (WAF) capabilities. You can implement security policies to protect against common attacks like SQL injection and cross-site scripting. Set up Cloud Armor with preconfigured rules and create custom rules for specific threat patterns. Enable rate limiting to prevent abuse and configure geo-based access controls if needed.

Service Account and Key Management:
Use Cloud IAM to create service accounts with minimal required permissions following the principle of least privilege. Implement Cloud KMS for encryption key management, creating separate key rings for different environments. Rotate service account keys regularly and use Workload Identity to securely connect GKE pods to Google Cloud services without storing credentials. Consider using Secret Manager for storing sensitive configuration data.

Database Backend:
Cloud Spanner provides a globally distributed, strongly consistent database that scales horizontally. Design the schema to optimize for your access patterns and use interleaved tables for parent-child relationships. Implement appropriate indexes and partitioning strategies. Configure multi-region deployments for high availability and configure backup schedules for disaster recovery.

Kubernetes Monitoring:
Set up GKE monitoring using Cloud Monitoring and Cloud Logging. Deploy Prometheus for detailed metrics collection and use custom dashboards to track key performance indicators. Monitor node health, pod status, and resource utilization. Configure alerting policies for critical metrics and implement log-based metrics for application-specific monitoring. Use Workload Identity for secure access to monitoring APIs.

Storage Cost Optimization:
Implement lifecycle policies in Cloud Storage to automatically transition objects between storage classes based on access patterns. Use Nearline storage for infrequently accessed data and Coldline for archival. Enable object versioning selectively and set up retention policies. Monitor storage usage through Cloud Monitoring and set up budget alerts to prevent unexpected costs.

Integration Strategy:
Connect these components securely using VPC networks and Cloud NAT where needed. Implement Cloud Load Balancing for traffic distribution and use Cloud CDN for content delivery. Create service mesh patterns with GKE to manage microservices communication. Use Cloud Endpoints or API Gateway to manage API access and implement OAuth 2.0 for authentication.

[yash9]

1. Increase Application and API Security

Tools :- Cloud Armor, Apigee / API Gateway, Identity-Aware Proxy (IAP), IA

• Cloud Armor protects your apps/APIs from DDoS attacks as well as web exploits (XSS, SQLi) via customizable WAF rules. You also have geo-blocking and rate limiting for traffic management options.
• Apigee (high level requirements) or API Gateway allows you to protect and scalably manage APIs—with native support for authentication (OAuth2/JWT), quotas and threat protection.
• You can use IAP (Identity-Aware Proxy) to restrict access to internal web applications based on user identity without VPN.
• IMO IAM needs to be least privilege; give users and services the permissions they really need, none more.

2. Securely Manage Service Accounts and Encryption Keys

Tools: IAM, Service Accounts, Workload Identity, Cloud KMS

• Create isolated Service Accounts per workload. Don't use default accounts.
• Use strict IAM roles — use pre-existing or custom roles with limited permissions.
• Use Workload Identity (more specifically in GKE) to enable apps to securely call Google Cloud APIs without dealing with service account keys.
• Cloud KMS provides protection for creating and maintaining encryption keys. Utilize CMEK (Customer Managed Encryption Keys) for added control, key rotation, and audit log logging.
• Turn on audit logs for IAM and KMS to track access and changes to keys / roles.

3. Create a Scalable and Durable Database Backend

Tool: Cloud Spanner (alternatives: Cloud SQL, Firestore)

• Cloud Spanner is an end-to-end managed global SQL database providing:

• Horizontal scaling
• Strong consistency
• 99.999% availability

• It 's ideal for applications that demand high write throughput and global availability.
• For lower budget / smaller workload use Cloud SQL (for MySQL/PostgreSQL) or Firestore (NoSQL).
• Schema design is key, don't make hotspots and follow Spanner best practices.

4. Monitor Kubernetes Clusters Effectively

Tools: GKE, Cloud Monitoring, Prometheus, Cloud Logging

• Simple container orchestration, auto-scaling, and security upgrades with Google Kubernetes Engine (GKE).
• Managed Prometheus on GKE offers deep insight into application performance -- use it to deploy custom metrics and alerts.
• Cloud Monitoring & Logging Offers Full-Stack visibility – read logs from nodes, containers and applications. Send alert based on CPU, memory, error rate, etc.
• GKE Autopilot is good if you're looking for less operational overhead — Google does the infrastructure — so you can focus on your application.

5. Reduce Costs Associated with Cloud Storage

Tools: Cloud Storage, Lifecycle Policies, Storage Insights, Object Versioning

• Choose the relevant storage class:

• Standard– for data that is accessed frequently
• Nearline, Coldline, Archive – for infrequent access or backup data

• Lifecycle policies can automatically migrate data to less expensive classes, or delete older files.
• Object Versioning may only be used at your own peril - you will get burned if you do it wrong.
•   Data security using Signed URLs and IAM policies. Ensure Data remains current and Available. 

Final Strategic Recommendations:

• Unlocks Severe Security Command Center provides continuous threat detection and monitoring your security posture. Click to activate.
•   Set budgets & alerts to monitor and control spending to Cloud Billing.
•   Terraform (Infrastructure as Code) allows for safe & reproducible environments via uniform deployments.

[Karanbyte07]

Hi everyone! I'm still learning but here how I approach it - 

To secure their apps we can use cloud armor for web attack protection also for DDoS and API gateway to manage and secure APIs with authentication and rate limiting. for access control service accounts roles help limit permissions and cloud KMS can manage encryption keys with automatic rotation. as  we know cloud spanner works for SQL workloads with global availability this can be ise for scalable and reliable database, and for serverless nosql firestore will be a good option. at last to save on storage costs I would suggest use different storage class based on access, enabling autoclass to automatically move data to cheaper tiers ... 

would love for any feedback... still learning and growing my skills with google cloud skills boost program...

[ayush007]

1. Enhance security for applications and APIs: Use Cloud Armor for DDoS protection and API Gateway for secure API management.
2. Manage service accounts and encryption keys securely: Utilize Service Accounts with least privilege access and Cloud KMS for encryption key management.
3. Build a scalable and durable database backend: Leverage Cloud Spanner for relational databases requiring strong consistency and horizontal scaling.
4. Monitor Kubernetes clusters effectively: Use GKE for Kubernetes management and Prometheus along with Google Cloud's operations suite for monitoring.
5. Optimize cloud storage costs: Use Cloud Storage with appropriate storage classes and Object Lifecycle Management to manage costs based on data access patterns.

[rutujaparde25]

For Securing applications and APIs, Cloud Armor is great to shield from DDoS and apply custom security rules. Pair it with API Gateway and IAP to lock down access securely.

Managing service accounts and encryption?                                                                                                                                                                          Definitely lean on IAM best practices (think: minimal access + naming conventions) and use Cloud KMS for encrypting sensitive data especially anything at rest or in transit.

For the backend, if you're expecting heavy traffic and need global availability, Cloud Spanner is solid. It’s a bit of an investment, but you get strong consistency and horizontal scaling out of the box.

Monitoring GKE clusters — go with Prometheus integrated into GKE, and maybe plug it into Grafana if you want custom dashboards. Also, don't skip Cloud Operations Suite for logs and alerts.

Cloud storage optimization?                                                                                                                                                                                                                  Apply storage class tiering (Standard, Nearline, Coldline, etc.) depending on how often you access the data. And set up lifecycle rules  they save money over time automatically.

[NiranjanMotagi]

To address these scaling challenges on Google Cloud:

Application & API Security:
Use Cloud Armor to protect applications from DDoS attacks and common vulnerabilities. Combine it with API Gateway and IAM-based authentication to secure and manage API access.

Service Account & Key Management:
Leverage Workload Identity Federation to reduce dependency on long-lived credentials. Enforce least privilege using IAM roles and securely manage encryption keys with Cloud KMS.

Scalable Database Backend:
Deploy Cloud Spanner for globally distributed, strongly consistent, and highly available relational database workloads. It scales horizontally and is built for mission-critical applications.

Kubernetes Monitoring:
Use GKE with Prometheus for real-time metrics collection. Integrate with Cloud Monitoring and Logging for comprehensive observability, alerting, and diagnostics.

Cloud Storage Cost Optimization:
Apply lifecycle rules in Cloud Storage to transition objects to Nearline, Coldline, or Archive classes based on access patterns. Use Storage Insights to audit usage and eliminate redundancy.

This architecture ensures security, reliability, and efficiency for scaling cloud-native applications.

[NiranjanMotagi]

To address these scaling challenges on Google Cloud:

Application & API Security:
Use Cloud Armor to protect applications from DDoS attacks and common vulnerabilities. Combine it with API Gateway and IAM-based authentication to secure and manage API access.

Service Account & Key Management:
Leverage Workload Identity Federation to reduce dependency on long-lived credentials. Enforce least privilege using IAM roles and securely manage encryption keys with Cloud KMS.

Scalable Database Backend:
Deploy Cloud Spanner for globally distributed, strongly consistent, and highly available relational database workloads. It scales horizontally and is built for mission-critical applications.

Kubernetes Monitoring:
Use GKE with Prometheus for real-time metrics collection. Integrate with Cloud Monitoring and Logging for comprehensive observability, alerting, and diagnostics.

Cloud Storage Cost Optimization:
Apply lifecycle rules in Cloud Storage to transition objects to Nearline, Cold line , or Archive classes based on access patterns. Use Storage Insights to audit usage and eliminate redundancy.

This architecture ensures security, reliability, and efficiency for scaling cloud-native applications.

[harshshirke]

1. Enhance Security for Applications and APIs
Use: [Cloud Armor] + Identity-Aware Proxy (IAP) + Apigee API Gateway

Cloud Armor protects your front-end from DDoS and OWASP Top 10 threats.

Apigee API Gateway secures and manages all your APIs with quota, auth, and logging.

Identity-Aware Proxy ensures only verified internal users can access back-office or admin UIs.

Bonus: Enable reCAPTCHA Enterprise to prevent bot submissions of fake internship reviews.

2. Manage Service Accounts and Encryption Keys Securely
Use: IAM Roles + Workload Identity + Cloud KMS

Workload Identity Federation links GKE workloads to IAM roles without managing service account keys.

Cloud KMS (Key Management Service) handles data encryption at rest and in transit.

Automatically rotate encryption keys and enforce access via fine-grained IAM policies.

3. Build a Scalable & Durable Database Backend
Use: Cloud Spanner

Horizontally scalable, strongly consistent, and globally distributed SQL database.

Ideal for managing user posts, tags, timestamps, and moderation flags at scale.

Use Spanner’s Change Streams for real-time moderation queues or analytics.

Alternative: Use Firestore (Native mode) if your write frequency is very high and the data model is semi-structured.

4. Monitor Kubernetes Clusters Effectively
Use: Google Kubernetes Engine (GKE) + Prometheus + Cloud Operations Suite

Deploy your app on GKE Autopilot for cost efficiency and auto-scaling.

Install Prometheus via GKE add-ons for custom metrics and alerting.

Use Cloud Logging + Cloud Monitoring for centralized, real-time observability.

Set up custom dashboards and SLOs with Cloud Monitoring.

5. Optimize Cloud Storage Costs
Use: Cloud Storage + Lifecycle Rules + Storage Classes

Store images, documents (like offer letters), and logs in Cloud Storage.

Apply lifecycle management rules to transition data from Standard → Nearline → Coldline → Archive based on access patterns.

Compress and deduplicate content automatically before storing.

Unique Optimization Strategy:
Use Cloud Build + Artifact Registry for CI/CD — it supports vulnerability scanning and minimizes build storage bloat.

Set up Budget Alerts + Recommender API to get real-time cost optimization tips (e.g., underutilized VM recommendations).

Implement Cloud Tasks for deferred processing of review moderation, tagging, or sentiment analysis to decouple request latency from back-end processing.

 For Anonymous User Posting:
Use Firebase Authentication (anonymous mode) or generate random session tokens securely via backend.

Store reviews with hashed IP (for abuse prevention) but never display or store identifying info.

Consider moderation queue with human or ML-based review (Perspective API or Vertex AI).

[aayushi_agarwal]

1.Enhance Security For Applications and APIs:

*API Gateway : secure API access 

*Cloud IAM(Identity and Access Management): Manage role and permissions at a fine-grained level.

2)MANAGE SERVICE ACCOUNTS AND ENCRYPTION KEYS SECURELY:

*Service Account : Grant Minimal level access to resources.

3)OPTIMIZE CLOUD STORAGE COSTS:

*Cloud storage classes:Use appropriate storage classes

4)MONITOR KUBERNETES CLUSTERS EFFECTIVELY:

*Google Kubernetes Engine(GKE): Use GKE For scable container

[Sanyagupta]

To scale company's cloud infrastructure efficiently, we’ll use key Google Cloud tools:

Security: Use Cloud Armor for DDoS protection and API Gateway/IAP to secure APIs and access. Manage access with IAM and Service Accounts.

Encryption: Leverage Cloud KMS for secure key management and enable Workload Identity Federation to reduce credential risks.

Database Scalability: Deploy Cloud Spanner for high-availability and global scalability; consider Cloud SQL or Bigtable based on workload needs.

Kubernetes Monitoring: Use GKE (Autopilot) for simplified scaling and Prometheus with Cloud Monitoring for visibility and alerting.

Storage Cost Optimization: Apply Cloud Storage lifecycle policies to auto-transition data across classes (Standard to Archive) and reduce costs.

Together, these tools create a secure, scalable, and cost-optimized cloud foundation ready for rapid growth.

[Bavanetha]

1. Protect Applications & APIs
    1)Cloud Armor → Turn on WAF rules + geo-blocking + rate limiting
    2)Apigee / API Gateway → Gate OAuth2/JWT, quotas, and traffic throttling
    3)IAP → Secure internal web apps with identity-based access
    4)Cloud IAM → Use least privilege access; don't use undifferentiated roles
2. Protect Service Accounts & Encryption Keys
    1)Dedicated Service Accounts → One per workload; never use default accounts
    2)IAM → Use custom roles with minimal access
    3)Workload Identity Federation → Authenticate non-GCP workloads without keys
    4)Cloud KMS (CMEK) → Use Customer-Managed Keys + enable automatic rotation
    5)Audit Logs → Turn on for KMS & IAM to monitor access
3. Build Scalable, Durable Database Backend
    1)Cloud Spanner → Best for global, transactional, high-availability apps (OLTP)
    2)Multi-region setup + follow partitioning/indexing best practices
    3)Cloud SQL → If you need managed MySQL/PostgreSQL (smaller workloads)
    4)Firestore → For NoSQL apps needing real-time sync and offline support
4. Efficient Monitoring of Kubernetes Clusters
     1)GKE Autopilot → Optimized scaling with fully managed Kubernetes
     2)Managed Prometheus on GKE → Built-in alerting + metrics collection
     3)Cloud Monitoring + Cloud Logging → Custom dashboards + centralized observability
     4)GKE Security Posture → Allow to identify misconfigs + vulnerabilities
5. Minimize Cloud Storage Costs
    1)Cloud Storage Classes:
       Standard → Recently accessed data
       Nearline, Coldline, Archive → Rarely accessed data
    2)Lifecycle Policies → Automatically transition or delete objects by age/access
    3)Object Versioning → Only enable where required
    4)Storage Insights → Monitor storage usage, spot waste
    5)IAM + Signed URLs → Restrict access to buckets/objects

[Rahul1619]

When it comes to keeping applications and APIs secure on Google Cloud, I’d like to suggest a fresh approach that goes beyond the usual firewalls and access controls. My idea is to use something called WebAssembly (Wasm) security modules as an extra layer of protection right where our cloud services connect with the outside world.

Here’s how it would work: Instead of putting all our trust in a single firewall or API gateway, we can build small, specialized Wasm modules that each handle a specific security task-like checking if someone is allowed in, making sure data looks safe, or spotting suspicious activity. These modules are super lightweight, run in their own safe “sandbox,” and can be updated instantly without shutting anything down. That means if a new security threat pops up, we can respond fast and keep everything running smoothly.

What’s really exciting is that these Wasm modules can work hand-in-hand with Google Cloud’s existing tools. For example, they can fetch encryption keys securely from Cloud KMS when needed, and they can send alerts if they spot anything unusual. Plus, because WebAssembly works the same way everywhere, we can use these modules across different parts of our system without worrying about compatibility.

In short, this approach gives us a flexible, modern way to strengthen security that can grow with the company. It’s not just about building higher walls-it’s about making our defenses smarter and more adaptable. I believe this could really help the company stay ahead of new threats as it scales up its cloud infrastructure.

[nischalstha08]

For locking down apps and APIs, Cloud Armor is essential. Layer your rules, definitely use Adaptive Protection, and always preview before enforcing. Slap Armor in front of API Gateway too. Inside, use strong auth (OAuth/JWT), rate limiting, and HTTPS everywhere. Adding reCAPTCHA helps stop bots early.

Managing access? Workload Identity Federation on GKE is the way – no more juggling service account keys, much safer. Centralize all your encryption key management with Cloud KMS and encrypt data both at rest and in transit.

Database scaling? If you need serious global scale and uptime, Cloud Spanner is built for it, just watch your schema design. Otherwise, Cloud SQL for relational or Firestore for NoSQL are great managed options.

Keep tabs on Kubernetes with GKE. Use Managed Prometheus (or roll your own) feeding into Cloud Monitoring & Logging. Set up proactive alerts! Definitely enable GKE security posture scanning, and consider Autopilot if you want less node management hassle.

Finally, control those Cloud Storage costs. Tier your data automatically using lifecycle rules (Standard -> Nearline -> Coldline -> Archive). Be smart about object versioning, use Storage Insights to understand usage, and lock down access with IAM and Signed URLs.

It's all interconnected – get these foundations solid, and scaling becomes much smoother. 

[Shikher-jain]

1. Enhance Security for Applications and APIs

• Google Cloud Armor
  Protect applications against DDoS and OWASP Top 10 threats. Apply custom security policies based on IP, region, or L7 parameters.

• API Gateway + Identity-Aware Proxy (IAP)
  Secure API endpoints with authentication and rate limiting. IAP ensures only authorized users can access backend services, enforcing context-aware access.

• VPC Service Controls
  Add an additional layer of defense by creating secure perimeters around your services like Cloud Storage and BigQuery, mitigating data exfiltration risks.

---

2. Manage Service Accounts and Encryption Keys Securely

• Service Accounts with IAM Roles
  Grant least privilege access per microservice using fine-grained IAM roles. Rotate service account keys periodically or, preferably, avoid static keys by using Workload Identity in GKE.

• Cloud Key Management Service (KMS)
  Centrally manage and rotate your cryptographic keys. Encrypt sensitive application data using envelope encryption. Consider Cloud HSM for hardware-backed key security.

---

3. Build a Scalable and Durable Database Backend

• Cloud Spanner
  A globally distributed, strongly consistent SQL database. Supports horizontal scaling with zero downtime, perfect for high-load transactional systems.

• Best Practices:

  • Use interleaved tables for hierarchical data.

  • Optimize queries with secondary indexes.

  • Enable autoscaling and regional replication.

---

4. Monitor Kubernetes Clusters Effectively

• Google Kubernetes Engine (GKE)
  Use GKE Autopilot for automated provisioning and scaling or Standard for full control. Leverage built-in security features like Binary Authorization.

• Prometheus + Cloud Monitoring (Stackdriver)
  Install Prometheus in GKE for real-time metrics, and integrate it with Cloud Monitoring to create dashboards, custom alerts, and incident responses.

• Cloud Logging
  Use structured logs with custom fields for faster debugging. Set up log-based alerts for anomalies or failures.

---

5. Optimize Cloud Storage Costs

• Cloud Storage with Lifecycle Rules
  Automatically move data to cost-efficient tiers:

  • Standard for active data

  • Nearline/Coldline for monthly/yearly access

  • Archive for long-term backups

• Storage Insights
  Enable usage analysis to detect stale data and identify opportunities to downgrade storage classes.

• Requester Pays
  Shift egress cost to users accessing your public data buckets.

[Shikher-jain]

1. Enhance Security for Applications and APIs

• Google Cloud Armor
  Protect applications against DDoS and OWASP Top 10 threats. Apply custom security policies based on IP, region, or L7 parameters.

• API Gateway + Identity-Aware Proxy (IAP)
  Secure API endpoints with authentication and rate limiting. IAP ensures only authorized users can access backend services, enforcing context-aware access.

• VPC Service Controls
  Add an additional layer of defense by creating secure perimeters around your services like Cloud Storage and BigQuery, mitigating data exfiltration risks.

2. Manage Service Accounts and Encryption Keys Securely

• Service Accounts with IAM Roles
  Grant least privilege access per microservice using fine-grained IAM roles. Rotate service account keys periodically or, preferably, avoid static keys by using Workload Identity in GKE.

• Cloud Key Management Service (KMS)
  Centrally manage and rotate your cryptographic keys. Encrypt sensitive application data using envelope encryption. Consider Cloud HSM for hardware-backed key security.

3. Build a Scalable and Durable Database Backend

• Cloud Spanner
  A globally distributed, strongly consistent SQL database. Supports horizontal scaling with zero downtime, perfect for high-load transactional systems.

• Best Practices:

  • Use interleaved tables for hierarchical data.

  • Optimize queries with secondary indexes.

  • Enable autoscaling and regional replication.

4. Monitor Kubernetes Clusters Effectively

• Google Kubernetes Engine (GKE)
  Use GKE Autopilot for automated provisioning and scaling or Standard for full control. Leverage built-in security features like Binary Authorization.

• Prometheus + Cloud Monitoring (Stackdriver)
  Install Prometheus in GKE for real-time metrics, and integrate it with Cloud Monitoring to create dashboards, custom alerts, and incident responses.

• Cloud Logging
  Use structured logs with custom fields for faster debugging. Set up log-based alerts for anomalies or failures.

5. Optimize Cloud Storage Costs

• Cloud Storage with Lifecycle Rules
  Automatically move data to cost-efficient tiers:

  • Standard for active data

  • Nearline/Coldline for monthly/yearly access

  • Archive for long-term backups

• Storage Insights
  Enable usage analysis to detect stale data and identify opportunities to downgrade storage classes.

• Requester Pays
  Shift egress cost to users accessing your public data buckets.

[Nischay1909]

I think one should think in the direction of cloud spanner because it is known for it's.                          1. It has Globally distributed SQL database                                                                                                       2.  It gives Horizontal scaling with no‑ops shading                                                                                         Some of its key features are .                                                                                                                            1.Strong consistency                                                                                                                                                2.High availability                                                                                                                                                    3.Managed backups & encryption                                                                                                                       4.Integrated change streams                                                                                                                            5.Automatic replication & failover                                                                                                                        It impacts the scaling of brand in the following way.                                                                                     1.No manual shading                                                                                                                                               2.Global apps are made easy                                                                                                                                3. Performance can be predicted                                                                                                                         4.Unified SQL interface                                                                                                                                   

[huhaksh]

1. API gateway for authentication and IAM for managing.

2. You can use GKE for it.

3. Cloud scanner for scalability.

4. GKE and cloud loging : can use for automationn and Collect and analyze logs from all pods, nodes.

5. cloud storage would be a great help and by using storage insights  it would help optimizing.

4. 

[Vishnu_94]

• Secure apps and APIs using Cloud Armor, API Gateway, and IAP to prevent threats and enforce authentication.

• Manage identity and encryption with IAM, Service Accounts, Cloud KMS, and Secret Manager for secure access and key handling.

• Build a resilient database backend using Cloud Spanner for global, scalable SQL storage with high availability.

• Monitor infrastructure with GKE, Prometheus, and Cloud Monitoring/Logging to track Kubernetes health and performance.

• Optimize storage costs using Cloud Storage lifecycle rules, smart storage class selection, and Storage Insights.

[Prachi_15]

To address scaling challenges, the company should use Cloud Armor to enhance application and API security, protecting against DDoS and web attacks. For identity and access management, leverage Service Accounts with IAM roles following the principle of least privilege, and use Cloud KMS to securely manage encryption keys.

To ensure a scalable and resilient database backend, adopt Cloud Spanner, which offers high availability and global consistency; Cloud SQL can be considered for smaller workloads. Deploy applications on Google Kubernetes Engine (GKE) and use Prometheus integrated with Cloud Monitoring to track cluster health, set alerts, and monitor performance. For cost optimization, use Cloud Storage with appropriate storage classes like Nearline or Archive, apply lifecycle management rules to automate data transitions, and utilize Budgets and Alerts to control spending.

These tools and strategies enable secure, scalable, and cost-efficient growth on Google Cloud.

[AryanSingh]

GOOGLE CLOUD TOOLS:

--> Security for applications and APIs- Cloud Armor, IAP, API Gateway along with VPC Service Controls

-->Manage service accounts and Key encryption- IAM, Service Accounts, Workload Identity and Cloud Key Management Service(KMS)

-->Scalable and durable database backend- Cloud Spanner, Cloud SQL

-->Monitor Kubernetes clusters- GKE, Prometheus, Cloud Monitoring and Logging

-->Optimize Cloud Storage Costs- Cloud Storage lifecycle rules, Insights, Coldline/Archive

[princeradadia]

it would be a long process but i would try my best to explain solution by using GCP services that i learned.

like using google cloud armor we can secure application against attacks like Distributed Denial of Service attacks and other web-based threats by enforcing Layer 7 security policies. Setting-up security policies using google cloud console or gcloud CLI. Specifying rules to allow or deny traffic based on IP addresses, geographic locations, or request attributes. Using security policy with our backend services behind a load balancer to filter incoming traffic. For advanced threat detection, enabling Adaptive Protection to analyze traffic patterns and suggest WAF rules.

Using service account and proper authentication like creating service account and granting proper roles and permissions using IAM policies. Giving service account some GCP services access resources like VMs, applications to maintain secure GCP services usage. 

Using cloud KMS we can set up encryption like making key ring in it and generating cryptographic key within it and defining proper IAM policies to access the keys also Using the keys we can encrypt data in services like Cloud Storage, Compute Engine, and Cloud SQL.

Using cloud spanner we can achieve scalable database solution like we can make cloud spanner instance selecting appropriate configuration regional or multi-regional designing database schema using SQL and creating database within spanner instance using client libraries by GCP we can connect our spanner database to application.

We can create GKE cluster and using yaml files kubernetes manifests we can define and deploy our application to cluster also leveraging GKE features like autoscaling, rolling updates and node pool management we can maintain application performance and availability.

Managing monitoring and alerting services in prometheus like enabling managed service in GCP deploying Prometheus exporters in our GKE cluster to collect metrics from your applications and Using PromQL to create dashboards and setting up alerting rules to monitor application performance and health.

Using cloud storage for cost-effective storage like creating storage buckets Defining lifecycle rules to automatically transition objects to lower-cost storage classes or delete them after a certain period and Configuring IAM policies to control access to the storage buckets and objects.

By implementing these GCP services, our company can enhance application security, manage authentication and encryption effectively, build a resilient and scalable database infrastructure, monitor Kubernetes clusters efficiently, and optimize storage costs as we scale our cloud infrastructure.

Thanks for a challange hope it could sum up a solution by GCP services that i learned.