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Unlock The Value of Big Data with Cisco Unified Computing System

Big Data is not just about gathering tons of data, the digital exhaust from the internet, social media, and customer records.  The real value is in being able to analyze the data to gain a desired business outcome.  

Screen Shot 2014-09-21 at 8.18.12 PMThose of us who follow the Big Data market closely never lack for something new to talk about. There is always a story about how a business is using Big Data in a different way or about some new breakthrough that has been achieved in the expansive big data ecosystem. The good news for all of us is, we have clearly only scratched the surface of the Big Data opportunity!

With the increasing momentum of the Internet of Everything (IoE) market transition, there will be 50 billion devices connected to the Internet by 2020—just five years from now. As billions of new people, processes, and things become connected, each connection will become a source of potentially powerful data to businesses and the public sector.  Organizations who can unlock the intelligence in this data can create new sources of competitive advantage, not just from more data but from better access to better data.

What we haven’t heard about – yet—are examples of enterprises that are applying the power of this data pervasively in their organizations:  giving them a competitive edge in marketing, supply chain, manufacturing, human resources, customer support, and many more departments. The enterprise that can apply the power of Big Data throughout their organization can create multiple and simultaneous sources of ongoing innovation—each one a constantly renewable or perpetual competitive edge. Looking forward, the companies that can accomplish this will be the ones setting the pace for the competition to follow.

Cisco has been working on making this vision of pervasive use of Big Data within enterprises a reality. We’d like to share this vision with you in an upcoming blog series and executive Webcast entitled, ‘Unlock Your Competitive Edge with Cisco Big Data Solutions’, that will air on October 21st at 9:00 AM PT.

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I have the honor of kicking off the multi-part blog series today. Each blog will focus on a specific Cisco solution our customers can utilize to unlock the power of their big data – enterprise-wide-- to deliver a competitive edge to our customers.  I’m going to start the discussion by highlighting the infrastructure implications for Big Data in the internet of Everything (IoE) era and focus on Cisco Unified Computing System initially.

Enterprises who want to make strategic use of data throughout their organizations will need to take advantage of the power of all types of data. As IoE increasingly takes root, organizations will be able to access data from virtually anywhere in their value chain. No longer restricted to small sets of structured, historical data, they’ll have more comprehensive and even real-time data including video surveillance information,  social media output, and sensor data that allow them to monitor behavior, performance, and preferences. These are just a few examples, but they underscore the fact that not all data is created equally. Real-time data coming in from a sensor may only be valuable for minutes, or even seconds – so it is critical to be able to act on that intelligence as quickly as possible. From an infrastructure standpoint, that means enterprises must be able to connect the computing resource as closely as possible to the many sources and users of data. At the same time, historical data will also continue to be critical to Big Data analytics.

Cisco UCS Common Platform Architecture for Big Data from Cisco Data Center

Cisco encourages our customers to take a long-term view—and select a Big Data infrastructure that is distributed, and designed for high scalability, management automation, outstanding performance, low TCO, and the comprehensive, security approach needed for the IoE era. And that infrastructure must be open—because there is tremendous innovation going on in this industry, and enterprises will want to be able to take full advantage of it.

Cisco UCS for Big DataOne of the foundational elements of our Big Data infrastructure is the Cisco Unified Computing System (UCS).  UCS integrated infrastructure uniquely combines server, network and storage access and has recently claimed the #1, x86 blade server market share position in the Americas. It’s this same innovation that propelled us to the leading blade market share position that we are directly applying to Big Data workloads.  With its highly efficient infrastructure, UCS lets enterprises manage up to 10,000 UCS servers as if they were a single pool of resources, so they can support the largest data clusters.

UCS Mini

Because enterprises will ultimately need to be able to capture intelligence from both data at rest in the data center and data at the edge of the network, Cisco’s broad portfolio of UCS systems gives our customers the flexibility to process data where it makes the most sense. For instance, our UCS 240 rack system has been extremely popular for Hadoop-based Big Data deployments at the data center core. And Cisco’s recently introduced UCS Mini is designed to process data at the edge of the network.

Because the entire UCS portfolio utilizes the same unified architecture, enterprises can choose the right compute configuration for the workload, with the advantage of being able to use the same powerful management and orchestration tools to speed deployment, maximize availability, and significantly lower your operating expenses.  Being able to leverage UCS Manager and Service Profiles, Unified Fabric and SingleConnect Technology, our Virtual interface card technology, and industry leading performance really set Cisco apart from our competition.

So, please consider this just an introduction to the first component of Cisco’s “bigger”, big data story. To hear more, please make plans to attend our upcoming webcast entitled,  ‘Unlock Your Competitive Edge With Cisco Big Data Solutions’ on October 21st.  

Register Now

Every Tuesday and Thursday from now until October 21st, we’ll post another blog in the series to provide you with additional details of Cisco’s full line of products, solutions and services.

View additional blogs in the series:

     9/25:    Unlock Big Data with Breakthroughs in Management Automation

     9/30:    Turbocharging New Hadoop Workloads with Application Centric Infrastructure

     10/2:    Enable Automated Big Data Workloads with Cisco Tidal Enterprise Scheduler

     10/7:    To Succeed with Big Data, Enterprises Must Drop an IT-Centric Mindset: Securing IoT Networks Requires New Thinking

     10/9:    Aligning Solutions to meet our Customers’ Data Challenges

    10/14:   Analytics for an IoE World

Please let me know if you have any comments or questions, or via Twitter at @CicconeScott.

 

 

 

 

 

 

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Top 10 ISV challenges with Cloud, Analytics, Mobile and Social Transformation

In my previous blog, I highlighted the need in ISV’s business transformation due to various changes in the market. Although ISVs are bound to face challenges as they shift their approach to application development, they must also be weary of the challenges that can come with other technological avenues, including cloud, analytics, mobile and social networks. The following are the top 10 challenges that I have seen ISVs struggling with in today’s market:

  • Domain 1 -- Infrastructure & Environment
    • In today’s cost-sensitive market with tight budgets, ISVs have to decide if there is a business case to build a Cloud to run their production software or host SaaS solution in a public Cloud or hosted Cloud. There are many qualitative and quantitative factors to consider. Qualitative analysis can include new or existing software solution, security, compliance, availability, global reach requirements, IP protection, existing IT resources in-house or lack there-of, etc. Quantitative analysis can include cost per user considering cost of compute, network, storage, support, training, software license, third party integration, human resource cost for development and support, etc.
    • It is easier to do the above analysis for Test environments, where you would need a large number of resources for a short period of testing time. Hence, public IaaS providers can be cost effective if there are no major concerns on Security, Compliance or IP-Protection. In such situations, ISVs can develop software using in-house environments and use public Cloud (or hybrid Cloud) for test environments.
    • ISVs should consider Cattle and Pet strategy (just like a cow in a cattle where if one cow dies, it gets replaced without any big impact to cattle, a server or a VM instance in cloud should be treated the same where if one server goes down, there should not be any impact on the functionalities of the cloud solution. This is unlike a pet -- or a traditional server in legacy environment -- where a pet requires care and create impact if something happens to it) in architecting the software for Cloud to reach higher availability. One should not have a Pet instance that cannot go down. Instead software solution should have failover capabilities and also load balancing capabilities so any server should be replaceable just like a cow in a Cattle. Following are some generic statistics of reliability in Cloud compare to Legacy environments:
      • Legacy has 99.9% reliability for Applications and 99.999% reliability for Infrastructure
      • Cloud has 99.0% reliability for Infrastructure and 99.999% reliability for Application
  • Domain 2 -- Virtualization & Abstraction
    • Evaluating if your software can live on a virtualized server or if it requires bare-metal server, can be the starting point in the Cloud journey. Not every software solution is designed to be on a virtualized server. In this case, it is a critical decision if one should redesign the software or develop it from the scratch or use container technology.
    • Questions, such as: “can (and should) your software do multi-tenancy?”are also very important. This decision can lead to overall impact on how you architect your software solution and evaluate price. Ability to do multi-tenancy can lead to reduced infrastructure to run your solution and hence, possibly reduced price to end customer. One should also evaluate impact of multi-tenancy on security that is required for ISV’s vertical industry. When a SaaS application handles sensitive data, ISVs must know and document how enterprise’s sensitive data is isolated from other tenants’ data. This analysis includes data at rest and data in-transit within the ISV’s SaaS environment, as well as in-transit across other untrusted networks.
  • Domain 3 -- Automation and Orchestration
    • Selecting the right tools for automation of policy-based orchestration, deployment and provisioning can lead to less manual steps, reduced time to setup new customers and enhanced speed to market.
    • Utilizing automation for release management can lead to less errors and smaller numbers of business interruption.
    • As high availability and less time between interruptions for disaster recovery are critical to keep customers in Cloud space, ISVs should have automation tools to do regular testing with simulated disaster situations to verify high availability.
  • Domain 4 -- Customer Interface
    • Since late 1990s, with introduction of Web, ISVs are forced to decide if software should have thick client or thin client or both. Now, with ubiquitous smart phones, popularity of mobile applications and with speedier releases of upgrades on popular mobile platforms such as Google Android, Apple IOS, etc., maintaining and upgrading mobile client can be substantial additional investment.
    • ISVs also need to make decisions on what should be the scope of the mobile client –
      • Should it be an independent software with full feature functionality of software solution, or
      • Should it be a hybrid solution where some feature functionalities are available on Mobile client while the rest is accessed remotely via web and executed in Cloud, or
      • Should Mobile client just be an additional device with remote web client?
    • In addition, with market trends towards integrating third party APIs to expand the feature functionalities of the software, role based identity management is critically important. Additional challenge is that ISVs have to develop flexible solution so they can adjust to different interpretation of different roles by different API providers.
  • Domain 5 -- Service Catalog
    • With SaaS, ISVs have to plan on how to price their software solution per user but also think about how to package the software solution and make it available using web based catalog. This catalog needs to have clear use cases that are easy to understand, aligned to vertical industry needs and price competitive to match customer’s willingness to pay. Moreover, though, any inclusion of third party software solution needs to be transparent to the user; it needs to be clearly defined in the legal language to reduce liability.
    • Development of such price & package is not a simple task. It is an art as one should create unique value perception for all use cases, be competitive, as well as make it easy for the user to decide and differentiate from competition to avoid price discussion instead of value. Moreover, this catalog may need to change regularly based on competitive forces and customer needs.
    • In addition to developing their own catalog, ISVs must also consider how their software solution can be integrated in Partner’s catalog so they can reach broader audience.  This requires considerations, such as how to price it to the value given by partner solution. This may require rethinking on the price as partner based use of ISV’s software solution may not include full feature functionalities.
  • Domain 6 -- Financial
    • Pricing software solution using Pay-per-use model is a challenge that is different from pricing for perpetual license. Pricing needs to be based on the market’s willingness to pay, as competition is just a click away. It also requires considerations and clear understanding that ISVs may not have many months to recover R&D cost due to competitive threats. Hence, it requires clear planning on how fast ISV can get enough customers to reach a breakeven point to cover R&D, customer acquisition & operation cost.
    • Compared to one-time billing for perpetual license, monthly or quarterly ongoing billing for pay-per use is a challenge and it has larger number of collection issues.
    • With the popularity of social media, even clarity and simplicity of regular bill-to-customer is important. Otherwise, ISV runs the risk of having a critical blogger targeting ISV billing practices and impacting reputation and moving customer’s opinion away from ISV. Such customer opinion also provides additional ammunition to competition. Hence, a bill should have enough details that are easy to understand, yet forces customers to see the value and possibly avoid easy comparison with competition.
    • In pay-per-use licensing, ISVs have to develop new strategy for revenue recognition and that can lead to impact on how sales compensations are designed.
    • If software solution includes third party vendors, ISVs need to do appropriate ongoing reporting to the vendor and also understand appropriate impact for tax purposes.
    • How long should ISVs let customer try software solution for free or have a promotional package is based on software solution maturity, market trends and direct competition. This decision alone can lead to high cost of customer acquisition and promotion.
    • Maximizing social networks such as Facebook and Twitter to understand market trends and develop appropriate reports for business impact is critical for today’s success and require additional skills and resources.
    • ISVs needs to develop intelligent reporting for customers, partners and its own management using analytics tools based on software solution. Moreover, making sense out of structured and non-structured data with variety, volume and velocity of data requires different reporting solutions such as use of Big Data Analytics. Each customer click that can span across ISV’s multiple systems and possibly multiple Cloud provider partners that are part of the solution can execute multiple transactions and produce multiple logs. Some of the key analysis that companies could consider based on business maturity to develop correlations and to make future business decisions are: log analysis (web, applications, transactions, database, IT Infrastructure, System Tracking, Errors, Intrusion detection logs), process analysis, user interaction analysis, real time alert & action analysis and historical event analysis. These solutions are not free and require appropriate in house resources such as Data scientists & Business analysts, infrastructure & software planning and investment.
  • Domain 7 -- Platform
    • With growth of Cloud, Linux has become a very popular OS to develop solutions on. One can find many IaaS and PaaS providers offering Linux offers on cost effective bases. That said, though Linux is popular, Windows is not too far away with support from Microsoft’s Azure and few other Cloud Providers. But other Unix flavors are becoming less and less popular day by day. Hence, ISVs have to consider if their software should be migrated to Linux or Windows if they are not developed on them.
    • Based on OS, one also needs to consider existing resource’s familiarity with popular application development platforms, frameworks and libraries. For example, ISVs may be able to find many resources that are familiar with Eclipse compared to other alternatives.
    • Similar to OS, database plays an important role in the stability, performance and cost of the software solution. Per CPU core pricing of Oracle may require additional look when open source database like MySQL has become very stable and popular for many use cases. Many ISVs have found it to be an acceptable alternative. By the way, such consideration may lead to redesign of the software and may not be appropriate for all conditions.
  • Domain 8 -- Application
    • ISVs have to develop a clear strategy that customers get hooked on by providing customers free or cost-effective training, or easy API based integration points for logging, reporting, identity integration, such that customers would not easily consider competition that is just a click away.
    • Decide if ISV should consider languages such as C#, C++, VB, Java or consider light weight scripting language such as Perl, Java Script, PHP, Ruby or Python or both is based on familiarity of existing development team, current code, modularity of the solution and available resources.
    • Large amount of source code is available via open source, and ISVs have to evaluate if it is appropriate for their development team to use it for faster time to market and also consider copy-right issues related to using such open source code.
    • ISVs have to revisit their software solution to understand that it has modular design to take advantage of heterogeneous components offered by the Cloud and also leads to appropriate planning for high availability.
  • Domain 9 -- Security and Compliance
    • As mentioned by Cloud Security Alliance for Application Security, there are four key metrics that apply for Cloud applications -- Compliance and Governance, Identity and Access,  Vulnerabilities and Patching, and Data Security. ISVs must ensure that needed metrics are available for Enterprise customers for their SaaS platform.
    • A good hacker can take advantage of the weakness in the development language for the software. Therefore, ISV needs to establish good coding practices such as input validation, authentication, authorization, configuration management, session management, cryptography, parameter manipulation,  exceptional management, appropriate protection of in-memory data, and audit & logging.
    • ISV should also document following key things for their Enterprise customers:
      • What Web application security standards (input validation, encoding output, preventing request forgery and information disclosure) are being followed by the ISV?
      • What application and infrastructure controls are in place to isolate the enterprise’s data from that of other tenants?
      • How many denial of service attacks were attempted and how were they  handled?
      • How do they manage identity?
      • How do they encrypt data (logs, between multiple application modules, between application and database and between application and third party API based use, etc)?
  • Domain 10 -- Organization, Governance and Process
    • Historically, software vendors are responsible for application development, feature and functionalities while customers are responsible for managing them in their own environment. With SaaS, operating and supporting is also part of ISV’s responsibilities. ISVs capability for continuous software development and with upfront considerations for operations and delivery of that software can allow capture of market opportunity faster and reduce time to get customer feedback. This DevOps software development methodology and considerations for operations is an important evolution compared to historically popular Waterfall or Agile methodologies. It is stated that DevOps methodology of software development reduces approximately 50% time as well as cost for long term operations support.
    • Impact of social network is tremendous and questions such as how are ISVs reaching out to potential target customers with social networking, how to support software online, how to maintain reputation online in the face of a crisis.
    • Many established ISVs have a sales force with tendency to hunt for the customers, transact the deal and leave. SaaS solution with pay-per-use licensing requires farming of the customers. In many ISV’s environment, this ongoing relationship building takes much more effort than sales is trained for, and would want to spend time per customer based on their quota size. Hence, ISVs have to plan appropriate sales strategy to keep sales force motivated.
    • For many ISVs, changing Sales compensations and training sales teams to sell pay-per-use license with minimal upfront revenue have been the most difficult part of this transformation. Established ISVs have to juggle to make sure that bottom line is not impacted too much and they can achieve good growth in subscription revenue for top line growth.
    • In this fast moving market with no permanent friends or foes, relationships for cooperation or competition, ISV has to continuously think who to partner with and how to structure partnership that is based on Customer value and aligned with ISV’s short & long term business strategy.
    • The need to move fast to improve software and remain a step ahead of the competition has lead  established ISVs to develop hybrid solutions while others SaaS based ISVs have become core business services in Cloud(i.e. Workday, Salesforce.com, google app engine etc.), and they are replacing traditional on-premises software vendors. Some ISVs have expanded their reach and capabilities using third party SaaS vendors echo systems, such as Salesforce.com.
  • Existing System Integration
    • Once ISV develops SaaS based solution, system integration with other ISV’s solutions, reporting needs requires modularized thinking and possibly different developer resources as not all integrations are based on simple solution such as REST API. Some still require custom API integrations that may be based on Java or C++. Moreover, such integration should also consider higher availability and scale needs for SaaS solutions.  Hence, ISV builds versus what ISV integrates into using third party API has become an important question of business decisions.
    • Success of ISVs does not only rely on the direct customers but also equality important are echo system partners. So ISVs also need to consider organic approach of today’s fast moving market environment and develop APIs for their key feature functionalities for partner’s to take advantage of. This is one of the very important considerations for DevOps methodology to address needs of development, operations and integration.  This ability to allow someone to integrate to your software using your API (possibly REST based) as part of echo system can offer immense opportunities for ISVs, as it automatically enables you to reach a wider customer base.

In short, it the pressure to continuously adding value when competition is one click away leads to a challenge of existence for ISV and a –poses the question: should ISV continue to be an ISV, or not? Small, agile and nimble ISVs can turn fast with the market trend but that can lead to not having sufficient time to develop efficient processes and procedures. Large and established ISVs have advantage of existing customers and well-oiled operations but changing faster with the time is always a challenge. This Ying and Yang of agility to meet market demand and efficiency to run the business is core to many ISV challenges.

After saying all of the above, not everything is bad for ISV business, as more and more ISVs are coming to market with their unique flavor of SaaS solution. There are many ways to make money in today’s market, such as faster customer reach due to internet, analytics, mobile and social networks as well as , enthusiastic responses from venture capitalists to invest in “good” SaaS based solutions. ISVs that understand the challenges explained and are weary of them will surely experience a positive change in their results.

Visit Cisco Services to learn more about how converging technology trends are shaping the way IT operates and delivers services. Be sure to join the conversation, #CiscoServices.

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Norway Looking to Lead in Customer Experience & Engagement

norway1

Norway’s longest running IT conference , IT-tinget concluded yesterday in the beautiful town of Tonsberg about an hour south of Oslo.

The event has been running for 31 years now and is organized and run by Cisco’s partner Evry.

This years theme is “#UserIsKing” , and Cisco hosted a special Retail Break out session along with Evry where Customer Experience and Engagement were the main focus. Read More »

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Revamping the MSE User Interface

As part of the WLC 8.0 release, we addressed customer comments and revamped the user interface (UI) for the MSE. We wanted to make it easier for customers using both MSE and PI to adjust to larger deployments. We also wanted to quicken the pace at which we could deliver features to the customers. Today I want to walk you through the landing page and configuration of the new MSE UI.

Landing Page

The landing page is the first thing one sees when logging into  the MSE UI. This page provides the user with a basic snapshot of system health, an easy way to launch the apps, and a quick status of the various services on MSE.

System Health

The new UI highlights important parameters like CPU and Memory usage in order to give the user an indication of the stress being handled by the MSE.

 mseui1 Read More »

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Analytics to Identify and Strengthen Organizational Collaboration and Drive Innovation

Companies with many employees face various challenges w.r.t. their size. One of these challenges is to identify key people, skills and information across (and outside) the organization and use them in the most effective way to drive innovation, new initiatives, but also sales.

Situation Today

The natural way for employees to cope with such a challenge is to build social networks (I mean networks of people not software) and collaborate across the organization. This organic social network building happens through various activities such as projects with colleagues, social activities, company events, etc… However, such social networks take time to create, and are typically not that extended. The effectiveness of these social networks is hard to measure (unless perhaps you equip your employees with location trackers). This social network building, I call the qualitative approach to organizational collaboration.

Connect and Collaborate

Connect with the right people inside and outside the enterprise

Many companies have deployed technology solutions (tools) to cope with the challenge described above. Companies have personnel directories that show employees’ groups and the official organization hierarchy. Some of these personnel directories allow users to add more personalized information (but this information is not always up to date). More sophisticated personnel directories (or other collaboration tools) also feature timelines of activities/tasks, blogging, integrated search, etc…. .Video conferencing enables people to connect people remotely. Despite these new social tools, email and mailing lists still play an important role in connecting people and disseminate information as well as external social networks and resources. All these tools provide a wealth of information. In essence: collaboration is Big Data.

Do all these social/collaborative enterprise tools help us doing our job better and promoting innovation? From a personal point of view I am tempted to say yes, but much more can be done. My main concern with most of these tools is the lack of analytics features to quickly identify user-relevant information or contacts. New tools -- and newer versions of already existing tools -- are starting to provide some of these capabilities, but IMO that is still not enough (or not accurate enough) to fully understand the evolving social networks or the relations between people and information (documents, emails, etc…).

What can be Improved

The goal of exposing more of the right analytics to end users would be, for a user, to faster gather insights, new ideas, and enable quicker decision making and eventually translate these insights and ideas to new opportunities, projects and/or costs savings.

Analyze and Correlate

Correlate different sources to identify information

To achieve this goal, users should be able to identify patterns in their organization’s data, specifically on threads or evolving thoughts and interactions that can be relevant for their particular projects or questions. In essence, analytics should foster more and improved collaboration with like-minded people, or people that share a common goal. As mentioned earlier, people naturally do this already, but in large organizations it is humanly impossible to scale this effectively and fast, without the help of analytics tools. This type of analytics I call the quantitative approach of organizational collaboration, which I see as complementary to the qualitative approach.

When I look for example at mailing lists or video conferencing, a few questions always pop up in my mind that modern enterprise collaboration tools should be able to answer in just a few clicks:

  1. What topics are trending during the last week/month? Perhaps type a topic in and get trend information or have the computer generate topics based on a context analysis of your posts or email conversations.
  2. How are the groups and hierarchies evolving over time (who is talking to who)? Can software recommend groups of people that are relevant for me and my projects?
  3. What people can be considered as experts on certain topics, based on their posts, replies, published articles, etc…?
  4. For particular topics, who are the top contributors and how do they relate to the experts? Are people clustering around certain topics?
  5. Who are the influencers/thought leaders, and how do they relate to experts?

From a strategic point of view companies can leverage analytics from social/collaborative tools to answer questions like:

  1. Are best practices shared across the organization between the appropriate groups?
  2. Is there an alignment between strategy and direction of the company?

This is not an exhaustive list and as a software engineer I think that an additional relevant feature for any tool should be the ability to provide an environment to mashup and integrate data by employees, to answer some of these questions.

How can it be Leveraged

Various groups and people (MIT, Virginia Tech, …) do research on this subject and translate this research into strategic insights at the enterprise level. The next step will be to provide the insights to individual employees as well. Enterprise tools with more sophisticated analytics capabilities (many focused on machine learning) are beginning to emerge. Perhaps the biggest challenge is integration of such capabilities across multiple internal and external tools and platforms.

Organizational collaboration is for me not limited to an enterprise environment. Groups with different affiliations who organize themselves as “virtual organizations” to work together towards common goals (for example, Open Source communities or standard bodies) can benefit from this type of analytics too.

To be more successful in capturing the value of collaboration, companies not only need to deploy the right tools, but also need to foster a mashup environment to leverage the organizational insight and tacit knowledge of its employees through analytics.

Special thanks to Marco Valente and Yannik Messerli for the discussions and insight on this subject.

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