Author

Ankur Mandal

March 11, 2024

Comparing Cloud Storage Solutions:

AWS, Azure, and GCP

Author

Ankur Mandal

4 min read
March 11, 2024

Navigating the landscape of cloud storage solutions is now a crucial task for organizations embracing cloud computing. While this shift has liberated them from physical server management, choosing the right cloud storage solution remains a complex decision due to the diverse advantages and challenges posed by different cloud service providers.

To simplify this process, our blog delves into an extensive analysis and comparison of storage options offered by three prominent cloud service giants: AWS, Azure, and GCP. We aim to provide insights that will empower you to make an informed choice aligned with your specific requirements.

The advent of cloud computing has revolutionized how organizations manage their data storage needs. The shift from conventional in-house infrastructure to cloud-based solutions has not only simplified operations but also provided unparalleled scalability and flexibility. Industry giants like AWS, Azure, and Google Cloud Platform (GCP) offer an extensive array of robust cloud storage options.

However, the challenge lies in discerning the nuances between these offerings to make well-informed decisions that align precisely with an organization's requirements. Understanding the significance of this decision-making process, we aim to guide you through the complexities of cloud storage solutions offered by AWS, Azure, and GCP. Through an in-depth analysis, we aim to equip businesses with the knowledge needed to navigate this multifaceted landscape. This knowledge will empower organizations to choose an efficient storage solution tailored perfectly to their unique objectives and needs.

Types Of Cloud Storage

To understand the difference between AWS, Azure, and GCP storage, we first need to understand the basics, i.e., types of cloud storage. 

1. Block Storage

Block storage utilizes a technique that involves dividing data into distinct blocks, each having a unique identifier, and storing them as independent entities on a server. These blocks are then efficiently dispersed across optimized locations within the cloud network, enhancing system performance. This method is particularly advantageous for managing large data volumes with low-latency demands, making it highly suitable for high-performance workloads, especially robust databases.

Use Cases Of Block Storage

Depending on Block Storage's advantages, it can be used in the following ways.

  • Database storage: Block storage stands out as the preferred choice for database storage due to its exceptional combination of speed, performance, and reliability. Its swift data handling capabilities make it a strong foundation for enterprise applications. Additionally, its seamless data block modification makes it ideal for files requiring frequent updates.
  • Server storage: Block storage systems showcase their versatility by distributing data across multiple volumes, particularly in server storage solutions. The ease of creating and formatting block-based storage volumes makes them an ideal choice for backend storage in virtualized systems. This feature allows easy attachment of a bare-metal server to a block, facilitating the creation of multiple virtual machines.
  • Email servers: For email servers, organizations turn to block storage technology for its exceptional performance and unwavering reliability. Acknowledging the critical nature of email data, block storage has become a standard practice for secure and efficient email storage within organizations.

2. Object Storage

Object storage is a fundamental architecture designed explicitly for extensive collections of unstructured data. This framework treats data pieces as separate entities or objects, each stored in distinct repositories alongside relevant metadata and a unique identifier. This systematic approach enables effortless data access and retrieval, enhancing efficiency in managing vast amounts of unstructured information.

Each object contains the following:

  • The Data: Objects encompass diverse types of information, from images to comprehensive manuals detailing complex processes like aircraft assembly. Unlike traditional file structures, objects transcend single files, representing interconnected bits and bytes that form a collective entity, accommodating subsets of files within.
  • Expandable Metadata: Metadata within object storage holds contextual information defining the data's nature, intended purpose, confidentiality levels, and other relevant details shaping its use. This metadata layer offers deeper insights into data significance, facilitating effective management.
  • Globally Unique Identifier: Each object in a distributed system received a globally unique identifier (GUID), a distinct 128-bit value. This GUID plays a vital role in locating the object, regardless of its physical location within the system. It enables efficient data access across various parts of a data center or globally distributed systems. This unique identifier ensures seamless dataretrieval in a connected and dispersed system.

Use Cases Of Object Storage

The many benefits of Object Storage make it a suitable choice for the following:

  • IoT management: Industries like manufacturing and healthcare, experiencing rapid growth in IoT data, find object storage crucial. Its ability to scale rapidly and retrieve data effortlessly meets the demands of managing substantial IoT-generated data..
  • Email storage: Object storage serves as an ideal repository for email storage, especially for organizations needing to preserve large volumes for historical records and compliance purposes. Its scalability and cost-effectiveness make it well-suited for managing extensive email storage needs.
  • Backup and recovery: Object storage is often the preferred choice for backup and recovery, prioritizing reliability over performance. Its efficiency in managing data backup and recovery requirements positions it as a dependable solution for organizations emphasizing data protection.

Choosing between object and block storage hinges on specific data storage and management needs. Object storage excels in storing unstructured data such as multimedia files, backups, and archives. It is ideal for distributed data storage, data analytics, and big data applications. Conversely, block storage is highly efficient for structured data storage, particularly databases and virtual machines. Its strong performance suits high-demand applications requiring low latency and high throughput.

3. Block Storage: AWS vs. Microsoft Azure vs. GCP

Diving into block storage options requires a foundational understanding of Solid State Drives (SSDs) and Hard Disk Drives (HDDs). These storage devices utilize distinct technologies.

Hard Disk Drives (HDDs): HDDs are traditional storage devices employing spinning platters for data reading and writing. They rely on magnetism to read and write data onto these rotating disks, offering storage capacity at relatively lower costs than SSDs.

Solid State Drives (SSDs): In contrast, SSDs utilize cutting-edge technology by storing data on memory chips, enabling instant access. Unlike HDDs, SSDs don’t rely on moving parts, resulting in faster data retrieval, reduced latency, and enhanced durability. Despite being more expensive per gigabyte than HDDs, SSDs offer higher speeds and efficiency in data storage and access.

Understanding these technologies sets the stage for exploring block storage options across AWS, Azure, and GCP, which often offer SSD and HDD variations tailored for different performance needs and use cases.

AWS

In Amazon Web Services (AWS), Elastic Block Store (EBS) offers a range of block storage alternatives, specifically Solid State Drive (SSD) and Hard Disk Drive (HDD) types. These options are tailored to suit distinct performance attributes and application scenarios. EBS storage opinions are categorized into the following.

SSD (Solid State Drive) Options

Amazon EBS General Purpose SSD (gp3):

  • Use Cases: Ideal for boot volumes, small to medium-sized databases, and development/test environments.
  • Key Features: Offers a balanced blend of performance and cost-effectiveness.
  • Customization: Users have the flexibility to independently adjust volume size and performance attributes such as IOPS and throughput.

Amazon EBS Provisioned IOPS SSD (io1):

  • Use Cases: Specifically designed for mission-critical applications like large relational and NoSQL databases.
  • Key Features: Provides consistent high performance.
  • Customization: Users can provision a specific level of IOPS (Input/Output Operations Per Second) according to workload requirements.

These options seem well-suited for varying application scenarios, allowing users to fine-tune storage performance based on their specific needs within AWS.

HDD (Hard Disk Drive) Options

Amazon EBS Throughput Optimized HDD (st1):

  • Use Cases: Suited for tasks requiring high data throughput like extensive data operations, data warehouses, and log processing.
  • Key Features:
  • Tailored for large-scale data processing tasks.
  • Offers cost-effective storage solutions for applications with high throughput requirements.

Amazon EBS Cold HDD (sc1):

  • Use Cases: Intended for scenarios with large volumes of infrequently accessed data.
  • Key Features:
  • Ideal for scenarios such as backup, long-term archival, or other cases involving infrequent data access.
  • Provides cost-effective storage options prioritizing cost optimization.

These options seem to offer cost-effective solutions for specific workload requirements within AWS, catering to different usage patterns and access frequencies.

Microsoft Azure

In Microsoft Azure, Azure Managed Disks predominantly offer block storage options for virtual machines (VMs). These disks are available in diverse types, each catering to different workloads and presenting a variety of performance characteristics.

SSD (Solid State Drive) Options

 Standard SSD Managed Disks: This option balances price and performance, suitable for workloads with moderate I/O requirements.

 Key Features:

  • Well-suited for enterprise workloads, like web servers, small to medium-sized databases, and development/test environments.
  • Offers a cost-effective solution for scenarios, not requiring maximum performance.

Premium SSD Managed Disks: Tailored for high-performance workloads, ensuring low latency and consistent I/O performance.

Key Features:

  • Ideal for mission-critical applications, large databases, and applications demanding high IOPS and throughput.
  • Provides better durability and lower latency compared to Standard SSD.

HDD (Hard Disk Drive) Options

Standard HDD Managed Disks: Offers a budget-friendly solution for workloads with low I/O requirements.

 Key Features:

  • Ideal for scenarios involving extensive data processing, backups, and applications prioritizing cost savings over high-performance storage.
  • Presents a balanced combination of cost-effectiveness and storage capacity.

Premium HDD Managed Disks: Specially designed for throughput-intensive workloads, offering a lower cost per GB compared to Premium SSD.

 Key Features:

  • Suitable for workloads demanding high throughput and large-scale data processing.
  • Offers a cost-effective solution for applications requiring substantial storage.

GCP

Google Cloud Platform (GCP) offers a range of block storage options through Persistent Disks, which serve diverse performance needs and use cases. With multiple disk types available, GCP efficiently caters to different requirements and ensures optimal storage solutions.

SSD (Solid State Drive) Choices

Standard Persistent Disks (SSD): Utilize SSDs to offer balanced performance suitable for various workloads.

 Key Features:

  • Adequate for general-purpose applications, web servers, and smaller databases.
  • Provides a good balance between cost and performance.

Premium Persistent Disks (SSD): Utilizes SSDs designed for high-performance workloads requiring low latency and consistent I/O performance.

 Key Features:

  • Ideal for mission-critical applications, large databases, and applications with high IOPS and throughput demands.
  • Offers better durability and lower latency compared to Standard SSD.

HDD (Hard Disk Drive) Options

Standard Persistent Disks (HDD): Utilizes HDDs to offer cost-effective storage solutions for workloads requiring lower performance.

 Key Features:

  • Ideal for scenarios involving large-scale data processing, backup, and applications prioritizing cost savings over high-performance storage.
  • Provides a balance between cost and storage capacity.

Local SSD: Physically attached to the VM host, providing exceptional high-performance and low-latency storage. However, it is important to note that they are temporary and do not retain data beyond the lifespan of the VM.

 Key Features:

  • Ideal for temporary data and workloads requiring high-speed and low-latency storage.
  • Unlike AWS and Azure, which offer data replication within the same region, GCP's Regional Persistent Disks automatically span multiple zones to ensure redundancy.

Key Factors For An Informed Decision

Now that we have listed the different block storage options for AWS, Azure, and GCP, we must understand their performance profiles, use cases, and other aspects that define them for each cloud service provider. 

SSD And HDD Volumes

AWS: Offers SSD volumes (gp3 and io1) for high-performance workloads and HDD volumes (st1 and sc1) for less frequently accessed data.

Azure: Provides SSD-managed disks (Standard SSD and Premium SSD) for low-latency workloads and HDD-managed disks (Standard HDD and Premium HDD) for cost-effective storage, balancing performance and price.

GCP: Similar to AWS and Azure, it offers SSD Persistent Disks and HDD Persistent Disks catering to high-performance and cost-effective storage needs.

Block Storage Volume Size

GCP: Leads in offering a broad range of volume sizes from 1GB to 64TB, providing exceptional flexibility.

AWS: Offers volumes ranging from 500GB to 16TB.

Azure: Provides volume sizes between 1GB and 32TB.

IOPS Rate

GCP: Boasts high IOPS rates with 100,000 IOPs for read operations and 80,000 IOPs for write operations, outperforming AWS and Azure.

AWS: It offers a maximum IOPS/volume of 64,000, which is competitive but slightly lower.

Azure: Presents a lower IOPS count of 5,000, comparatively less in terms of performance.

Throughput:

  • GCP: Provides competitive throughput with 480 MBps for reads and 240 MBps for writes, slightly lower than Azure.
  • Azure: Offers a range of 750 MBps.
  • AWS: Provides a maximum throughput of 500 MBps.

Pricing

Understanding pricing in the cloud storage industry can be complex, but analyzing the cost per GB/month for different tiers reveals interesting details. 

Azure: Starts from $0.018 per GB/month, making it a cost-effective choice for block storage.

GCP: Offers competitive pricing at $0.02 per GB/month.

AWS: Priced at $0.15/GB/month, relatively higher than Azure and GCP.

So, if you are looking for a cost-effective block storage solution, we suggest going with Azure for its reasonable pricing.

AWS

  • HDD: $0.045 per GB per month of provisioned storage
  • SSD: $0.018 per GB/month

Azure

  • HDD: $0.03 per GB per month
  • SSD: $0.15/GB/month

GCP

  • HDD: $0.04/GB-month
  • SSD: $0.02 per GB per month

Wondering what to choose as the right block storage option?

The trade-off between cost and performance is significant when choosing between block storage options. SSD volumes, managed disks, and persistent disks provide superior performance but come at a higher cost per GB compared to their HDD counterparts. Opt for SSD-based solutions—like SSD Volumes, Managed Disks, or Persistent Disks—when your applications require high IOPS, low latency, and consistent performance. Conversely, if you're dealing with large-scale data processing and prioritize cost efficiency, considering HDD-based options—such as HDD Volumes, Managed Disks, or Persistent Disks—would be more suitable.

Are you confused between AWS, Azure, or GCP block storage?

Navigating between AWS, Azure, or GCP for block storage can be overwhelming due to each provider's extensive features. The optimal choice hinges on your specific use case, performance needs, and the overall cloud environment where your applications operate. Here are tailored examples to assist you in your decision-making process:

AWS EBS stands out for its seamless volume snapshots and support for critical functionalities like Amazon EBS Multi-Attach. This makes it an excellent choice for configurations requiring high availability.

Azure provides a diverse range of availability options, encompassing Standard and Premium SSDs, Ultra Disks tailored for high-performance workloads, and Shared Disks designed for clustering scenarios. However, it's crucial to note that certain features might not be universally accessible across all regions. Therefore, carefully evaluating regional availability based on your deployment needs is advisable.

Similarly, Google Cloud Persistent Disks streamline backup and disaster recovery processes with efficient snapshot capabilities. Nevertheless, planning for redundancy and failover is vital since Persistent Disks are closely tied to specific zones.

Each provider offers distinct advantages, so it's essential to thoroughly understand your specific requirements and the nuances of each service's offerings to make an informed decision. Taking into account your use case, performance criteria, and geographical considerations will help you select the most suitable block storage solution.

Object Storage: AWS vs. Microsoft Azure vs. GCP

Now that we have a fair idea of block storage options in AWS, Azure, and GCP, let us discuss the object storage options.

AWS

AWS offers S3 as its object storage solution. It is a flexible solution for storing and accessing data effortlessly through the internet. Incorporating a user-friendly web services interface facilitates web-scale computing for developers. Boasting an exceptional durability rate of 99.999999999% and a remarkable object availability of 99.99%, Amazon S3 guarantees strong and dependable data management. Furthermore, it supports storing individual files of significant sizes, reaching up to 5 terabytes. S3 has the following features.

  • Data protection: Amazon S3, an infrastructure designed for object storage, empowers IT teams with a reliable and scalable platform that prioritizes the durability and security of stored data. To ensure utmost protection, multiple defensive measures are deployed, such as:
  • Data Encryption
  • Versioning
  • Cross-Region Replication
  • Transfer Acceleration

These features collectively reinforce the integrity and accessibility of your data within the Amazon S3 environment.

  • Bucket Policy: A bucket policy in Amazon S3 refers to an Identity and Access Management (IAM) policy that can authorize or limit permissions for your S3 resources. This policy goes beyond individual files and lets you establish security rules for multiple files within a specific bucket. This allows you to effectively deny access to the specified user, ensuring they cannot access the designated bucket.
  • Lifecycle management: In the lifecycle management domain, Amazon S3 employs a defined set of rules to determine actions for a specific group of objects. This well-thought-out approach enables seamless object management and storage, emphasizing resource optimization for cost-effectiveness. It involves two types of actions- transaction actions and expiration actions.

Amazon S3 has the following applications.

  • Backup and Archival: Organizations can confidently depend on the durability and availability of S3 for secure and persistent data storage. Thanks to its redundant architecture and distributed storage capabilities, critical data can be stored with swift and safe access.
  • Content Distribution and Hosting: By leveraging S3's extensive network of edge locations, content creators can effortlessly distribute files to end-users across the globe. This not only reduces latency but also improves the overall user experience. Additionally, by integrating with content delivery networks (CDNs), content distribution is further expedited, guaranteeing fast and efficient file delivery.
  • Disaster Recovery: S3's cross-region replication feature allows businesses to conveniently duplicate data across different Amazon regions, ensuring its safety against potential regional disasters. This allows organizations to efficiently restore data from replicated copies in S3 in the event of a catastrophe, effectively reducing downtime and minimizing data loss.

Microsoft Azure

Azure Blob Storage is Microsoft's object storage solution for the cloud. Microsoft Azure Blob Storage offers internet-accessible storage for various data types. It is particularly efficient for storing media files like audio and video and dynamic and frequently updated data such as log files. In this storage environment, the term "blob," which stands for a large binary object, refers to data stored in binary format.

Some of the key features of Azure Blob Storage are:

  • Scalability: Blob Storage effortlessly manages data of all sizes, streamlining the storage and administration of extensive volumes of unstructured data in the cloud.
  • Durability: Blob Storage ensures outstanding data durability by maintaining multiple replicas across diverse data centers, ensuring data availability and recovery.
  • Security: Blob Storage emphasizes data security with its multi-layered protection approach. This includes data encryption at rest and in transit, role-based access control, and shared access signatures.
  • Integration: Blob Storage integrates with various Azure services, such as Azure Data Factory, Azure Functions, and Azure Stream Analytics. It also seamlessly integrates with third-party tools, establishing itself as a flexible solution suitable for various use cases.
  • Object-level Tiering: Blob Storage introduces the capability to organize data into hot, cold, and archive tiers, empowering users to effectively store and manage data based on its frequency of use and temporal sensitivity.
  • Advanced Data Management Features: With Blob Storage, users can access advanced data management features like object versioning, deletion policies, lifecycle management, and event-driven workflows. These features enhance control and efficiency in managing data within the storage system.

Blob storage is a useful storage technology that can be used for the following business technology operations.

  • Data ingestion: Azure Blob Storage enables effortless data ingestion into platforms like SQL Azure databases, HDInsight, and Azure Machine Learning. Teams striving to integrate stored data into applications, particularly those leveraging ML and Hadoop, can take advantage of the strong ingestion capabilities offered by Azure Blob Storage.
  • Backup: Businesses can store backup copies of data in a storage account within Azure Blob Storage, ensuring quick retrieval during system downtime. It is essential to select an account type optimized for low latencies when dealing with high-performance applications or needing immediate restoration. Furthermore, users can restore SQL Server data to Azure Blob Storage directly.
  • Big data: Blob storage is essential for enterprises dealing with substantial data, particularly during significant big data analyses. With its ability to handle unstructured data, blob storage efficiently caters to various formats of enterprise information. The stored data is easily accessible for extensive analytics on a large scale.

GCP

Google Cloud Storage is a reliable and adaptable service provided by Google Cloud Platform that caters to the storage needs of various organizations. This service offers exceptional scalability and durability and is developed specifically for handling unstructured data such as files, images, videos, backups, and logs. With extensive features for efficient data storage, retrieval, and management, Google Cloud Storage emerges as an ideal solution for many applications and use cases.

Google Cloud Storage is known for its robust and adaptable object storage solution, which offers a range of impressive features:

  • Scalability: Enjoy the convenience of virtually unlimited storage capacity, allowing easy adjustment to changing storage requirements.
  • Durability and Availability: Your data stored in Google Cloud Storage is distributed across multiple data centers, ensuring high durability and availability.
  • Storage Classes: Choose from various storage classes, including Standard, Nearline, Coldline, and Archive, to find the perfect balance between performance and cost.
  • Data Lifecycle Management: Easily define lifecycle policies to automate object transitions between storage classes or remove unnecessary objects.
  • Data Encryption: Rest assured with encryption at rest, featuring support for server-side encryption and the option for customer-managed encryption keys.
  • Data Access Control: Benefit from fine-grained access control through Identity and Access Management (IAM), providing you with the power to control data access.
  • Data Versioning: With support for versioning, Google Cloud Storage allows the seamless management of various versions of an object, ensuring its consistency over time.
  • Object Metadata: Google Cloud Storage enables attaching custom metadata to objects, assisting in storing additional information associated with the data.
  • Geo-Redundancy: Opt for geo-redundant storage options to replicate data across multiple geographical regions. This feature enhances disaster recovery capabilities by ensuring data availability from different locations.
  • Data Transfer: Google Cloud Storage simplifies data transfer processes by offering a range of efficient methods such as APIs, SDKs, command-line tools, and graphical interfaces, enabling seamless data movement in and out of the storage platform.

The following are the use cases of Google Cloud Storage.

  • Backups and Archives: Google Cloud Storage provides a swift, budget-friendly, and remarkably robust storage solution specifically designed for data accessed less than once a month. This solution perfectly suits businesses seeking cost-efficient backups and long-term archives while guaranteeing immediate access whenever required. It is essential to acknowledge that the advantages of using Cloud Storage for backups surpass mere data recovery purposes, as it leverages exceptional millisecond latency across all storage classes, along with a unified API that ensures seamless access to your valuable information.
  • Content storage and delivery: Geo-redundant storage, in combination with high-quality availability and performance, is highly effective in providing low-latency, high-quality content to users spread across various locations. Google Cloud Storage is proficient in ensuring the availability and efficient data transfer required to stream audio or video to applications or websites seamlessly.
  • Repository for analytics and ML: Optimal availability and performance within a single region are paramount for computing, analytics, and machine learning workloads exclusive to that region. Cloud Storage ensures reliable support by offering high availability and performance, guaranteeing strong consistency. This unique attribute instills confidence and precision in analytics workloads, making Cloud Storage a dependable choice.

Wondering which one to choose- AWS, Azure, or GCP?

Choosing between AWS, Azure, or GCP for your cloud services can be daunting, but understanding their strengths can help.

AWS excels in durability and availability, making it a great choice for robust, reliable storage solutions.

GCP stands out with its pay-per-second billing model, offering potentially cost-efficient alternatives. This adaptable pricing structure allows precise payment for resources used, particularly beneficial for fluctuating workloads.

A multi-cloud strategy could also be advantageous. For instance, integrating Azure Functions with Amazon S3 allows seamless triggering of events or code execution in response to S3 bucket events. Being serverless and supporting multiple programming languages, Azure Functions offers flexibility in defining logic triggered by object changes in S3.

This integration benefits scenarios requiring specific actions or custom code execution in response to S3 changes, enhancing application functionality and automation. Combining S3's scalable storage with Azure Functions' event-driven compute capability creates a robust solution, eliminating the need to manage server infrastructure.

Opting for multiple cloud providers reduces vendor lock-in and offers flexibility based on performance, cost, and features. It also aids in compliance with global data sovereignty regulations, ensuring data management alignment with diverse regulatory frameworks worldwide.

By leveraging the strengths of different cloud providers and employing a multi-cloud strategy, you not only enhance functionality and reduce costs but also ensure compliance and flexibility across global deployments.

Save On Storage Cost With Block Storage Auto-Scaler

Optimizing block storage costs across cloud service providers, whether it's AWS's EBS cost optimization, Azure storage cost optimization, or cost optimization of GCP's Persistent Disk, is crucial to prevent soaring cloud bills. This optimization cuts costs and enhances performance, resource efficiency, and overall operational effectiveness, providing organizations with a competitive edge in the dynamic cloud landscape.

Our analysis of AWS and Azure users revealed significant insights into how storage impacts overall cloud expenditure. In Azure specifically, a striking discovery emerged: a mere 35% of disk storage exhibited active usage, indicating an excessive allocation of 65% of disk space.

This revelation underscores the importance of scrutinizing and fine-tuning storage allocations. Organizations can significantly reduce wasted resources and optimize costs by accurately assessing and aligning storage capacities with actual utilization patterns. Employing strategies such as rightsizing storage, implementing tiered storage solutions, and leveraging automation for resource management can effectively curtail unnecessary expenses while ensuring adequate performance and scalability.

During our exploration of the Amazon Web Services (AWS) cost structure, we made an intriguing finding. The expenditure breakdown indicated that the Elastic Block Store (EBS) accounted for 15% of the organization's overall cloud costs. Furthermore, our analysis revealed an average disk utilization rate of 25%.

Moreover, despite massive overprovisioning, the organization faced at least one downtime per quarter. Additionally, this overprovisioning was also leading to underutilized and idle volumes. This means organizations were paying for the resources they were not using. 

Organizations commonly allocate excessive storage resources for two key reasons:

  • Limited capabilities of Cloud Service Providers (CSPs): Achieving storage optimization in a Cloud environment often requires specialized tools not readily available within CSPs offerings. This lack of robust optimization features can lead to a reliance on DevOps teams, demanding time-consuming efforts to manage and optimize storage effectively. Relying solely on CSP tools can also complicate everyday operations and regular tasks..
  • Ensure application uptime: Overprovisioning becomes a common strategy to safeguard applications, ensuring their availability and minimizing potential disruptions.. 

However, this approach often leads to excessive resource allocation, resulting in inflated expenses due to the underutilization or non-utilization of the allocated capacity.

A study conducted by StormForge highlighted that a significant portion of cloud spending, about 48%, is wasted due to over-provisioning and the complexity of cloud infrastructure. This misallocation of resources diverts approximately $17 billion per year that could have been directed toward crucial business initiatives.

While cloud service providers allow for expanding storage resources as needed, there's no direct method for shrinking them. Manual adjustments are possible but are time-consuming and prone to errors due to the complexity involved.

Addressing this need for automated storage optimization, Lucidity has introduced an innovative solution—the industry's first autonomous storage orchestration platform.

Lucidity's Block Storage Auto-Scaler dynamically adjusts storage resources based on fluctuating demands, enabling both expansion and shrinkage. By effectively managing capacity, Lucidity's Auto-Scaler eliminates the need for overprovisioning, significantly reducing storage costs. This solution offers a streamlined approach to optimize storage resources, enhancing efficiency and cost-effectiveness for organizations operating in the cloud.

Lucidity's Live Block Storage Auto-Scaler is an adaptive solution designed to seamlessly adjust to evolving storage needs, ensuring optimal performance without downtime and facilitating efficient capacity modifications on your cloud service provider's block storage. 

The benefits of Lucidity's Live Block Storage Auto-Scaler include:

  • Zero downtime: The Auto-Scaler optimizes costs by dynamically adjusting storage resources without manual intervention. This ensures uninterrupted service as storage seamlessly adapts to changing demands, minimizing disruptions. The implementation process is swift and hassle-free, with the Lucidity Auto-Scaler agent consuming minimal resources—only around 2% of CPU or RAM usage.
  • Automated expansion and storage: Lucidity's solution automates storage scaling, ensuring continuous availability in response to fluctuating demands. Whether faced with sudden spikes or reduced activity, the Auto-Scaler adjusts storage resources, optimizing efficiency and aligning with workload requirements.
  • 70% reduction in storage costs: Leveraging Lucidity's automated scaling can yield substantial savings, potentially reducing storage expenses by up to 70%. The auto-scaler significantly improves disk utilization, enhancing it from 35% to an impressive 80%, leading to substantial cost reductions.

We helped Allegis discover Azure wastage

Allegis, a multinational organization specializing in talent management, had integrated Azure cloud services into its operations but faced excessive expenses related to cloud storage across over 200 subscriptions. They aimed to improve cloud utilization efficiency, recognizing the critical role of effective storage and compute resource management in achieving cost optimization.

The challenge lies in acquiring detailed insights into storage metrics. Identifying dormant or unused disks manually would burden the DevOps team significantly in terms of time and effort. Seeking a streamlined solution to prevent cost escalations, Allegis approached us for Azure cost optimization tailored to their specific requirements.

Our agentless audit solution is seamlessly integrated within 25 minutes with a simple click. This streamlined approach swiftly revealed valuable findings and recommendations, alleviating the manual burden and providing crucial insights into dormant or unused disks. This initiative contributed to significant cost reductions, addressing Allegis's need for improved cloud utilization efficiency.

  • Cloud Storage Waste: A staggering 74% of the total cloud storage has been identified as waste.
  • Overprovisioned Resources: An astonishing 57% of this waste can be attributed to overprovisioning resources, leading to a mere 18.3% utilization of the available disk space.
  • Idle or Unused Resources: A noteworthy 41% of the resources have been discovered idle or unused. These resources are either unattached to a virtual machine or connected to a stopped VM.

Utilizing Lucidity Audit, Allegis successfully achieved an in-depth understanding of its Azure disks. We helped accurately pinpoint five resources suffering from excessive utilization; they proactively mitigated the risk of severe downtime. Prompt measures were taken to ensure seamless operations, rendering any last-minute Site Reliability Engineering (SRE) interventions unnecessary.

After the wastage report from Allegis was received, our Lucidity Auto-Scaler was swiftly put into action. Through close collaboration with Allegis, we successfully applied strategic deployment techniques that delivered exceptional results—a notable 60% decrease in storage expenses.

Unlock Cloud Efficiency With Block Storage Optimization

Optimizing block storage is paramount, regardless of the chosen storage option or cloud service provider. The efficiency and cost-effectiveness of storage resources significantly influence overall performance and financial outcomes. Lucidity Auto-Scaler presents the solution your organization requires to ensure the smooth adaptation of storage infrastructure to dynamic demands, leading to improved operational efficiency and reduced costs.

Why wait? Schedule a demo with Lucidity today and unlock the potential of automation to generate substantial savings for your business. Discover firsthand how our solution can revolutionize your storage optimization strategy and drive efficiency in your cloud infrastructure.

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